Updated on 2024/11/15

Information

 

写真a

 
NIIOKA HIROHIKO
 
Organization
Data-Driven Innovation Initiative Professor
Title
Professor
Contact information
メールアドレス
Tel
0926426475

Degree

  • Ph.D.

Research History

  • 2022年10月 - 2024年1月大阪大学, 情報科学研究科 情報数理学専攻, 特任准教授 2017年11月 - 2022年9月大阪大学 データビリティフロンティア機構, 特任准教授 2012年10月 - 2017年10月大阪大学, 大学院基礎工学研究科 機能創成専攻 生体工学領域, 助教 2009年4月 - 2012年9月大阪大学, ナノサイエンスデザイン教育研究センター, 特任助教   

Awards

  • 若手研究奨励賞 (Young lnvestigator Award:YIA)

    2023.10   第49回日本神経内分泌学会学術集会   Deep Learningを利用した多能性幹細胞の分化予測

  • 若手講演奨励賞

    2023.10   第46回日本生体医工学会中国四国支部大会   甲状腺細胞診支援AIによる人間の診断能力向上に関する検討

  • 優秀演題賞

    2023.7   第64回日本臨床細胞学会(春季大会)   自己教師あり学習と少数教師ラベルを用いた甲状腺細胞診画像分類

  • コニカミノルタ科学技術振興財団・日本生体医工学会大会奨励賞

    2023.5   第62回日本生体医工学会大会   自己教師あり学習を用いた甲状腺細胞診画像の自動診断補助システム開発

  • レーザー学会奨励賞

    2020.10   レーザー学会第547回研究会   非線形ラマン散乱硬性内視鏡と深層学習による神経イメージング装置の開発

  • Cypos賞金賞

    2020.5   第79回日本医学放射線学会(JRS)総会   Grad-CAMsを用いたブラックボックスの解明:人工知能は肺癌CT画像のどこみているのか?

  • Young Investigator’s Award

    2019.6   第58回日本生体医工学会大会   深紫外励起テルビウム蛍光画像の人工知能解析による癌リンパ節転移検出

  • ポスターセッション優秀賞

    2018.2   第10回呼吸機能イメージング研究会学術集会   人工知能(深層学習)を用いた肺癌の画像診断:上皮内腺癌(AIS)、微小浸潤性腺癌(MIA)、浸潤性腺癌(IVA)の鑑別

  • 講演奨励賞

    2017.3   第64回応用物理学会春季学術講演会   Er添加ナノ粒子の高次非線形応答を用いた蛍光イメージング

  • 優秀ポスター賞

    2016.11   第39回日本分子生物学会年会   Deep Learningによるフラビウイルスの分類

  • Best Poster Presentation Award 2nd Prize

    2016.10   11th Asian Biohydrogen & Biogas Symposium (ABBS 2016)   Best Poster Presentation Award 2nd Prize

  • ZEISS賞

    2016.9   第25回日本バイオイメージング学会学術集会   位相差顕微鏡像と畳み込みニューラルネットワークを用いたC2C12細胞の分化識別

  • SI2015優秀講演賞

    2015.12   第16回計測自動制御学会システムインテグレーション部門講演会   Deep Learningを用いたヒトミトコンドリアDNAの分類

  • 平成26年度 第八回風戸研究奨励賞

    2015.2   公益財団法人 風戸研究奨励会   光・電子相関顕微鏡法のためのプローブ開発と細胞イメージング応用

  • ベストプレゼンテーション賞

    2014.11   Optics and Photonics Japan 2014   4次ラマン顕微鏡を用いた非中心対称性結晶の選択的観察

  • Best Paper Award

    2014.2   Japan Taiwan Bilateral Conference on Biomedical and Plasmonic Imaging   Visible to near-infrared luminescent nanoparticles for multimodal bioimaging on nanometer to millimeter scale

  • Best Poster Award

    2014.2   1st. KANSAI Nanoscience and Nanotechnology International Symposium   Y2O3-based nanophosphors for multi-colored cathodoluminescence and up-conversion luminescence bioimaging

  • 日本機械学会フェロー賞

    2013.11   日本機械学会 第24回バイオフロンティア講演会   マルチスケール生体イメージングを目指したカソードルミネッセンス・アップコンバージョンナノ蛍光体の作製

  • 若手ポスター賞

    2013.11   平成25年度日本分光学会年次講演会   透過電子顕微鏡を用いたカソードルミネッセンスバイオイメージング

  • 第35回応用物理学会論文奨励賞

    2013.9   公益社団法人 応用物理学会 JSAP   Multicolor Cathodoluminescence Microscopy for Biological Imaging with Nanophosphors

  • 大阪大学総長奨励賞

    2013.8   大阪大学  

  • ベストプレゼンテーション賞

    2012.3   平成23年度 日本機械学会関西学生会学生員卒業研究発表講演会   多色カソードルミネッセンスナノイメージングのための無機ナノ粒子の作製

  • 若手ポスター賞

    2010.11   公益社団法人 日本分光学会   Pt基板上自己組織化単分子膜の高感度/高分解能SHGイメージング

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Papers

  • The implementation of CycleGAN-assisted image translation in deep UV-excited fluorescence microscopy improves the accuracy of lymph node metastasis detection, facilitating intraoperative diagnosis.

    新岡 宏彦

    Transactions of Japanese Society for Medical and Biological Engineering   Annual62 ( Abstract )   125_1 - 125_1   2024   ISSN:1347443X eISSN:18814379

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    Language:Japanese   Publisher:Japanese Society for Medical and Biological Engineering  

    <p>This study addresses the necessity for improved intraoperative diagnostic systems in surgery. The prevalent frozen section procedure is hindered by poor quality and time consumption, leading to exploration of alternatives. Microscopy with ultraviolet surface excitation (MUSE) stands out as a rapid and cost-effective imaging technique. However, labeling MUSE images of unfixed specimens poses challenges for pathologists, hindering supervised learning for AI. To overcome this, a deep-learning pipeline for lymph node metastasis detection is proposed. CycleGAN translate MUSE images of unfixed lymph nodes to formalin‐fixed paraffin‐embedded (FFPE) sample, and diagnostic prediction is performed using deep convolutional neural network (CNN) trained on previous FFPE samples stored in hospital. The pipeline achieves an 84.6% average accuracy, an 18.3% improvement over the CNN-only model. The CycleGAN-driven modality translation can be applied to various intraoperative diagnostic imaging systems, addressing the difficulty in labeling new modality images.</p>

    DOI: 10.11239/jsmbe.annual62.125_1

    CiNii Research

  • Self-Supervised Learning for Feature Extraction from Glomerular Images and Disease Classification with Minimal Annotations

    Abe M., Niioka H., Matsumoto A., Katsuma Y., Imai A., Okushima H., Ozaki S., Fujii N., Oka K., Sakaguchi Y., Inoue K., Isaka Y., Matsui I.

    Journal of the American Society of Nephrology   2024   ISSN:10466673

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    Background: Deep learning has great potential in digital kidney pathology. However, its effectiveness depends heavily on the availability of extensively labeled datasets, which are often limited due to the specialized knowledge and time required for their creation. This limitation hinders the widespread application of deep learning for the analysis of kidney biopsy images. Methods: We applied self-distillation with no labels (DINO), a self-supervised learning method, to a dataset of 10,423 glomerular images obtained from 384 PAS-stained kidney biopsy slides. Glomerular features extracted from the DINO-pretrained backbone were visualized using principal component analysis (PCA). We then performed classification tasks by adding either k-nearest neighbor (kNN) classifiers or linear head layers to the DINOpretrained or ImageNet-pretrained backbones. These models were trained on our labeled classification dataset. Performance was evaluated using metrics such as the area under the receiver operating characteristic curve (ROC-AUC). The classification tasks encompassed four disease categories (minimal change disease, mesangial proliferative glomerulonephritis, membranous nephropathy, and diabetic nephropathy) as well as clinical parameters such as hypertension, proteinuria, and hematuria. Results: PCA visualization revealed distinct principal components corresponding to different glomerular structures, demonstrating the capability of the DINO-pretrained backbone to capture morphological features. In disease classification, the DINO-pretrained transferred model (ROC-AUC = 0.93) outperformed the ImageNet-pretrained fine-tuned model (ROCAUC = 0.89). When the labeled data were limited, the ImageNet-pretrained fine-tuned model's ROC-AUC dropped to 0.76 (95% confidence interval [CI], 0.72-0.80), whereas the DINO-pretrained transferred model maintained superior performance (ROC-AUC 0.88, 95% CI 0.86-0.90). The DINO-pretrained transferred model also exhibited higher AUCs for the classification of several clinical parameters. External validation using two independent datasets confirmed DINO pre-training's superiority, particularly when labeled data were limited. Conclusions: The application of DINO to unlabeled PAS-stained glomerular images facilitated the extraction of histological features that can be effectively utilized for disease classification.

    DOI: 10.1681/ASN.0000000514

    Scopus

    PubMed

  • Deep UV-excited fluorescence microscopy installed with CycleGAN-assisted image translation enhances precise detection of lymph node metastasis towards rapid intraoperative diagnosis Reviewed

    Junya Sato, Tatsuya Matsumoto, Ryuta Nakao, Hideo Tanaka, Hajime Nagahara, Hirohiko Niioka, Tetsuro Takamatsu

    Scientific Reports   13 ( 1 )   2023.12

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    Language:Others   Publishing type:Research paper (scientific journal)  

    Abstract

    Rapid and precise intraoperative diagnosing systems are required for improving surgical outcomes and patient prognosis. Because of the poor quality and time-intensive process of the prevalent frozen section procedure, various intraoperative diagnostic imaging systems have been explored. Microscopy with ultraviolet surface excitation (MUSE) is an inexpensive, maintenance-free, and rapid imaging technique that yields images like thin-sectioned samples without sectioning. However, pathologists find it nearly impossible to assign diagnostic labels to MUSE images of unfixed specimens; thus, AI for intraoperative diagnosis cannot be trained in a supervised learning manner. In this study, we propose a deep-learning pipeline model for lymph node metastasis detection, in which CycleGAN translate MUSE images of unfixed lymph nodes to formalin-fixed paraffin-embedded (FFPE) sample, and diagnostic prediction is performed using deep convolutional neural network trained on FFPE sample images. Our pipeline yielded an average accuracy of 84.6% when using each of the three deep convolutional neural networks, which is a 18.3% increase over the classification-only model without CycleGAN. The modality translation to FFPE sample images using CycleGAN can be applied to various intraoperative diagnostic imaging systems and eliminate the difficulty for pathologists in labeling new modality images in clinical sites. We anticipate our pipeline to be a starting point for accurate rapid intraoperative diagnostic systems for new imaging modalities, leading to healthcare quality improvement.

    DOI: 10.1038/s41598-023-48319-7

  • Martensite transformation triggered with intense THz pulses

    Masaya Nagai, Yuhei Higashitani, Masaaki Ashida, Koichi Kusakabe, Hirohiko Niioka, Azusa N. Hattori, Hidekazu Tanaka, Goro Isoyama, Norimasa Ozaki

    2023 48th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)   2023.9

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    Language:Others   Publishing type:Research paper (other academic)  

    DOI: 10.1109/irmmw-thz57677.2023.10298936

  • Terahertz-induced martensitic transformation in partially stabilized zirconia Reviewed

    Masaya Nagai, Yuhei Higashitani, Masaaki Ashida, Koichi Kusakabe, Hirohiko Niioka, Azusa N. Hattori, Hidekazu Tanaka, Goro Isoyama, Norimasa Ozaki

    Communications Physics   6 ( 1 )   2023.4

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    Terahertz-induced martensitic transformation in partially stabilized zirconia
    Abstract

    Martensitic crystal structures are usually obtained by rapid thermal quenching of certain alloys, which induces stress and subsequent shear deformation. Here, we demonstrate that it is also possible to intentionally excite a suitable transverse acoustic phonon mode to induce a local shear deformation. We irradiate the surface of a partially stabilized zirconia plate with intense terahertz pulses and verify martensitic transformation from the tetragonal to the monoclinic phases by Raman spectroscopy and the observed destructive spallation of the zirconia microcrystals. We calculate the phonon modes in tetragonal zirconia and determine the decay channel that triggers the transformation. The phonon mode required for the martensitic transformation can be excited via the Klemens process. Since terahertz pulses can induce a specific local shear deformation beyond thermal equilibrium, they can be used to elucidate phase transformation mechanisms with approaches based on nonlinear phononics.

    DOI: 10.1038/s42005-023-01207-y

  • Application of deep learning as an ancillary diagnostic tool for thyroid FNA cytology Reviewed

    Mitsuyoshi Hirokawa, Hirohiko Niioka, Ayana Suzuki, Masatoshi Abe, Yusuke Arai, Hajime Nagahara, Akira Miyauchi, Takashi Akamizu

    Cancer Cytopathology   131 ( 4 )   217 - 225   2022.12

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    Application of deep learning as an ancillary diagnostic tool for thyroid FNA cytology

    DOI: 10.1002/cncy.22669

  • Automated diagnosis of optical coherence tomography imaging on plaque vulnerability and its relation to clinical outcomes in coronary artery disease Reviewed

    Hirohiko Niioka, Teruyoshi Kume, Takashi Kubo, Tsunenari Soeda, Makoto Watanabe, Ryotaro Yamada, Yasushi Sakata, Yoshihiro Miyamoto, Bowen Wang, Hajime Nagahara, Jun Miyake, Takashi Akasaka, Yoshihiko Saito, Shiro Uemura

    Scientific Reports   12 ( 1 )   2022.8

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    Abstract

    This study sought to develop a deep learning-based diagnostic algorithm for plaque vulnerability by analyzing intravascular optical coherence tomography (OCT) images and to investigate the relation between AI-plaque vulnerability and clinical outcomes in patients with coronary artery disease (CAD). A total of 1791 study patients who underwent OCT examinations were recruited from a multicenter clinical database, and the OCT images were first labeled as either normal, a stable plaque, or a vulnerable plaque by expert cardiologists. A DenseNet-121-based deep learning algorithm for plaque characterization was developed by training with 44,947 prelabeled OCT images, and demonstrated excellent differentiation among normal, stable plaques, and vulnerable plaques. Patients who were diagnosed with vulnerable plaques by the algorithm had a significantly higher rate of both events from the OCT-observed segments and clinical events than the patients with normal and stable plaque (log-rank p < 0.001). On the multivariate logistic regression analyses, the OCT diagnosis of a vulnerable plaque by the algorithm was independently associated with both types of events (p = 0.047 and p < 0.001, respectively). The AI analysis of intracoronary OCT imaging can assist cardiologists in diagnosing plaque vulnerability and identifying CAD patients with a high probability of occurrence of future clinical events.

    DOI: 10.1038/s41598-022-18473-5

  • AI を用いた甲状腺細胞診支援システムの開発と利用 Reviewed

    廣川満良, 新岡宏彦, 鈴木彩菜, 安部政俊, 式見彰浩, 長原一, 宮内昭

    Journal of the Japanese Society of Clinical Cytology   61 ( 3 )   200 - 207   2022.5

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

    Development and utilization of AI for differential diagnosis in cytol- ogy of the thyroid(ADDICT)

    DOI: 10.5795/jjscc.61.200

  • 【次世代の甲状腺細胞診】AIを用いた甲状腺細胞診支援システムの開発と利用

    廣川 満良, 新岡 宏彦, 鈴木 彩菜, 安部 政俊, 式見 彰浩, 長原 一, 宮内 昭

    日本臨床細胞学会雑誌   61 ( 3 )   200 - 207   2022.5   ISSN:0387-1193

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    Language:Japanese   Publisher:(公社)日本臨床細胞学会  

    目的:AIを用いた甲状腺細胞診支援システムの開発とその利用について述べる。方法:細胞画像139695枚のデータを資料として用いた。画像分類モデルとして事前学習済みのEfficient Net-B0を使用し、データ拡張には水平反転と垂直反転、Cutmix、Augmixを用いた。5分割交差検証でモデルの学習を行い、予測確率の平均値をテストデータの最終予測確率とした。成績:良性病変の精度(PR AUC=0.99)が最も良く、低分化癌と髄様癌以外の腫瘍のPR AUCは0.9以上であった。濾胞腺腫と濾胞癌の正答率はそれぞれ81%、94%で、両者が区別された。t-SNEによる特徴量の次元圧縮結果ではリンパ腫は三つ、未分化癌は二つのグループに分かれた。Grad-CAMの結果から、AIは腫瘍細胞の核に注目していることが判明した。意義不明例を予測させると、良性・悪性の判断においては92.3%が的中していた。結論:AIを用いた画像解析は意義不明や濾胞性腫瘍の補助診断法として期待できる。今後はインターネット上で甲状腺細胞診を行うプラットフォームを構築する予定である。(著者抄録)

  • Near real-time nerve visualization using coherent Raman scattering rigid endoscope and deep learning-based image processing for nerve-sparing surgery Reviewed

    Naoki Yamato, Hirohiko Niioka, Jun Miyake, Mamoru Hashimoto

    Biomedical Vibrational Spectroscopy 2022: Advances in Research and Industry   2022.3

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    Language:English   Publishing type:Research paper (other academic)  

    DOI: 10.1117/12.2609483

  • Diagnostic performance for pulmonary adenocarcinoma on CT: comparison of radiologists with and without three-dimensional convolutional neural network Reviewed International journal

    Masahiro Yanagawa, Hirohiko Niioka, Masahiko Kusumoto, Kazuo Awai, Mitsuko Tsubamoto, Yukihisa Satoh, Tomo Miyata, Yuriko Yoshida, Noriko Kikuchi, Akinori Hata, Shohei Yamasaki, Shoji Kido, Hajime Nagahara, Jun Miyake, Noriyuki Tomiyama

    European Radiology   31 ( 4 )   1978 - 1986   2021.4

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    Language:English   Publishing type:Research paper (scientific journal)  

    OBJECTIVES: To compare diagnostic performance for pulmonary invasive adenocarcinoma among radiologists with and without three-dimensional convolutional neural network (3D-CNN). METHODS: Enrolled were 285 patients with adenocarcinoma in situ (AIS, n = 75), minimally invasive adenocarcinoma (MIA, n = 58), and invasive adenocarcinoma (IVA, n = 152). A 3D-CNN model was constructed with seven convolution-pooling and two max-pooling layers and fully connected layers, in which batch normalization, residual connection, and global average pooling were used. Only the flipping process was performed for augmentation. The output layer comprised two nodes for two conditions (AIS/MIA and IVA) according to prognosis. Diagnostic performance of the 3D-CNN model in 285 patients was calculated using nested 10-fold cross-validation. In 90 of 285 patients, results from each radiologist (R1, R2, and R3; with 9, 14, and 26 years of experience, respectively) with and without the 3D-CNN model were statistically compared. RESULTS: Without the 3D-CNN model, accuracy, sensitivity, and specificity of the radiologists were as follows: R1, 70.0%, 52.1%, and 90.5%; R2, 72.2%, 75%, and 69%; and R3, 74.4%, 89.6%, and 57.1%, respectively. With the 3D-CNN model, accuracy, sensitivity, and specificity of the radiologists were as follows: R1, 72.2%, 77.1%, and 66.7%; R2, 74.4%, 85.4%, and 61.9%; and R3, 74.4%, 93.8%, and 52.4%, respectively. Diagnostic performance of each radiologist with and without the 3D-CNN model had no significant difference (p > 0.88), but the accuracy of R1 and R2 was significantly higher with than without the 3D-CNN model (p < 0.01). CONCLUSIONS: The 3D-CNN model can support a less-experienced radiologist to improve diagnostic accuracy for pulmonary invasive adenocarcinoma without deteriorating any diagnostic performances. KEY POINTS: • The 3D-CNN model is a non-invasive method for predicting pulmonary invasive adenocarcinoma in CT images with high sensitivity. • Diagnostic accuracy by a less-experienced radiologist was better with the 3D-CNN model than without the model.

    DOI: 10.1007/s00330-020-07339-x

  • Improvement of nerve imaging speed with coherent anti-Stokes Raman scattering rigid endoscope using deep-learning noise reduction Reviewed

    Naoki Yamato, Hirohiko Niioka, Jun Miyake, Mamoru Hashimoto

    Scientific Reports   10 ( 1 )   2020.12

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    <title>Abstract</title>A coherent anti-Stokes Raman scattering (CARS) rigid endoscope was developed to visualize peripheral nerves without labeling for nerve-sparing endoscopic surgery. The developed CARS endoscope had a problem with low imaging speed, i.e. low imaging rate. In this study, we demonstrate that noise reduction with deep learning boosts the nerve imaging speed with CARS endoscopy. We employ fine-tuning and ensemble learning and compare deep learning models with three different architectures. In the fine-tuning strategy, deep learning models are pre-trained with CARS microscopy nerve images and retrained with CARS endoscopy nerve images to compensate for the small dataset of CARS endoscopy images. We propose using the equivalent imaging rate (EIR) as a new evaluation metric for quantitatively and directly assessing the imaging rate improvement by deep learning models. The highest EIR of the deep learning model was 7.0 images/min, which was 5 times higher than that of the raw endoscopic image of 1.4 images/min. We believe that the improvement of the nerve imaging speed will open up the possibility of reducing postoperative dysfunction by intraoperative nerve identification.

    DOI: 10.1038/s41598-020-72241-x

  • Following Embryonic Stem Cells, Their Differentiated Progeny, and Cell-State Changes During iPS Reprogramming by Raman Spectroscopy Reviewed International journal

    Arno Germond, Yulia Panina, Mikio Shiga, Hirohiko Niioka, Tomonobu M. Watanabe

    Analytical Chemistry   92 ( 22 )   14915 - 14923   2020.11

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    Monitoring cell-state transition in pluripotent cells is invaluable for application and basic research. In this study, we demonstrate the pertinence of noninvasive, label-free Raman spectroscopy to monitor and characterize the cell-state transition of mouse stem cells undergoing reprogramming. Using an isogenic cell line of mouse stem cells, reprogramming from neuronal cells was performed, and we showcase a comparative analysis of living single-cell spectral data of the original stem cells, their neuronal progenitors, and reprogrammed cells. Neural network, regression models, and ratiometric analyses were used to discriminate the cell states and extract several important biomarkers specific to differentiation or reprogramming. Our results indicated that the Raman spectrum allowed us to build a low-dimensional space allowing us to monitor and characterize the dynamics of cell-state transition at a single-cell level, scattered in heterogeneous populations. The ability of monitoring pluripotency by Raman spectroscopy and distinguishing differences between ES and reprogrammed cells is also discussed.

    DOI: 10.1021/acs.analchem.0c01800

  • Red-Fluorescent Pt Nanoclusters for Detecting and Imaging HER2 in Breast Cancer Cells Reviewed

    Shin-ichi Tanaka, Hiroki Wadati, Kazuhisa Sato, Hidehiro Yasuda, Hirohiko Niioka

    ACS Omega   5 ( 37 )   23718 - 23723   2020.9

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    Overexpression of human epidermal growth factor receptor 2 (HER2) is associated with more frequent cancer recurrence and metastasis. Sensitive sensing of HER2 in living breast cancer cells is crucial in the early stages of cancer and to further understand its role in cells. Biomedical imaging has become an indispensable tool in the fields of early cancer diagnosis and therapy. In this study, we designed and synthesized platinum (Pt) nanocluster bionanoprobes with red emission (Ex/Em = 535/630 nm) for fluorescence imaging of HER2. Our Pt nanoclusters, which were synthesized using polyamidoamine (PAMAM) dendrimer and preequilibration, exhibited approximately 1% quantum yield and possessed low cytotoxicity, ultrasmall size, and excellent photostability. Furthermore, combined with ProteinA as an adapter protein, we developed Pt bionanoprobes with minimal nonspecific binding and utilized them as fluorescent probes for highly sensitive optical imaging of HER2 at the cellular level. More importantly, molecular probes with long-wavelength emission have allowed visualization of deep anatomical features because of enhanced tissue penetration and a decrease in background noise from tissue scattering. Our Pt nanoclusters are promising fluorescent probes for biomedical applications.

    DOI: 10.1021/acsomega.0c02578

  • Nerve Segmentation with Deep Learning from Label-Free Endoscopic Images Obtained Using Coherent Anti-Stokes Raman Scattering Reviewed

    Naoki Yamato, Mana Matsuya, Hirohiko Niioka, Jun Miyake, Mamoru Hashimoto

    Biomolecules   10 ( 7 )   1012 - 1012   2020.7

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    Semantic segmentation with deep learning to extract nerves from label-free endoscopic images obtained using coherent anti-Stokes Raman scattering (CARS) for nerve-sparing surgery is described. We developed a CARS rigid endoscope in order to identify the exact location of peripheral nerves in surgery. Myelinated nerves are visualized with a CARS lipid signal in a label-free manner. Because the lipid distribution includes other tissues as well as nerves, nerve segmentation is required to achieve nerve-sparing surgery. We propose using U-Net with a VGG16 encoder as a deep learning model and pre-training with fluorescence images, which visualize the lipid distribution similar to CARS images, before fine-tuning with a small dataset of CARS endoscopy images. For nerve segmentation, we used 24 CARS and 1,818 fluorescence nerve images of three rabbit prostates. We achieved label-free nerve segmentation with a mean accuracy of 0.962 and an F 1 value of 0.860. Pre-training on fluorescence images significantly improved the performance of nerve segmentation in terms of the mean accuracy and F 1 value ( p < 0 . 05 ). Nerve segmentation of label-free endoscopic images will allow for safer endoscopic surgery, while reducing dysfunction and improving prognosis after surgery.

    DOI: 10.3390/biom10071012

  • Convolutional Neural Network Can Recognize Drug Resistance of Single Cancer Cells. Reviewed International journal

    Kiminori Yanagisawa, Masayasu Toratani, Ayumu Asai, Masamitsu Konno, Hirohiko Niioka, Tsunekazu Mizushima, Taroh Satoh, Jun Miyake, Kazuhiko Ogawa, Andrea Vecchione, Yuichiro Doki, Hidetoshi Eguchi, Hideshi Ishii

    International journal of molecular sciences   21 ( 9 )   2020.4

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    It is known that single or isolated tumor cells enter cancer patients' circulatory systems. These circulating tumor cells (CTCs) are thought to be an effective tool for diagnosing cancer malignancy. However, handling CTC samples and evaluating CTC sequence analysis results are challenging. Recently, the convolutional neural network (CNN) model, a type of deep learning model, has been increasingly adopted for medical image analyses. However, it is controversial whether cell characteristics can be identified at the single-cell level by using machine learning methods. This study intends to verify whether an AI system could classify the sensitivity of anticancer drugs, based on cell morphology during culture. We constructed a CNN based on the VGG16 model that could predict the efficiency of antitumor drugs at the single-cell level. The machine learning revealed that our model could identify the effects of antitumor drugs with ~0.80 accuracies. Our results show that, in the future, realizing precision medicine to identify effective antitumor drugs for individual patients may be possible by extracting CTCs from blood and performing classification by using an AI system.

    DOI: 10.3390/ijms21093166

  • Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network Reviewed International journal

    Tatsuya Matsumoto, Hirohiko Niioka(equally contributed), Yasuaki Kumamoto, Junya Sato, Osamu Inamori, Ryuta Nakao, Yoshinori Harada, Eiichi Konishi, Eigo Otsuji, Hideo Tanaka, Jun Miyake, Tetsuro Takamatsu

    Scientific Reports   9 ( 1 )   16912-1 - 16912-12   2019.11

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    Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network
    Deep-UV (DUV) excitation fluorescence microscopy has potential to provide rapid diagnosis with simple technique comparing to conventional histopathology based on hematoxylin and eosin (H&E) staining. We established a fluorescent staining protocol for DUV excitation fluorescence imaging that has enabled clear discrimination of nucleoplasm, nucleolus, and cytoplasm. Fluorescence images of metastasis-positive/-negative lymph nodes of gastric cancer patients were used for patch-based training with a deep neural network (DNN) based on Inception-v3 architecture. The performance on small patches of the fluorescence images was comparable with that of H&E images. Gradient-weighted class activation mapping analysis revealed the areas where the trained model identified metastatic lesions in the images containing cancer cells. We extended the method to large-size image analysis enabling accurate detection of metastatic lesions. We discuss usefulness of DUV excitation fluorescence imaging with the aid of DNN analysis, which is promising for assisting pathologists in assessment of lymph node metastasis.

    DOI: 10.1038/s41598-019-53405-w

  • Excitation of erbium-doped nanoparticles in 1550-nm wavelength region for deep tissue imaging with reduced degradation of spatial resolution Reviewed

    Yamanaka, M., Niioka, H., Furukawa, T., Nishizawa, N.

    Journal of Biomedical Optics   24 ( 7 )   070501-1 - 070501-4   2019.7

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    DOI: 10.1117/1.JBO.24.7.070501

  • Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma: A preliminary study. Reviewed International journal

    Masahiro Yanagawa, Hirohiko Niioka, Akinori Hata, Noriko Kikuchi, Osamu Honda, Hiroyuki Kurakami, Eiichi Morii, Masayuki Noguchi, Yoshiyuki Watanabe, Jun Miyake, Noriyuki Tomiyama

    Medicine   98 ( 25 )   e16119   2019.6

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    To compare results for radiological prediction of pathological invasiveness in lung adenocarcinoma between radiologists and a deep learning (DL) system.Ninety patients (50 men, 40 women; mean age, 66 years; range, 40-88 years) who underwent pre-operative chest computed tomography (CT) with 0.625-mm slice thickness were included in this retrospective study. Twenty-four cases of adenocarcinoma in situ (AIS), 20 cases of minimally invasive adenocarcinoma (MIA), and 46 cases of invasive adenocarcinoma (IVA) were pathologically diagnosed. Three radiologists of different levels of experience diagnosed each nodule by using previously documented CT findings to predict pathological invasiveness. DL was structured using a 3-dimensional (3D) convolutional neural network (3D-CNN) constructed with 2 successive pairs of convolution and max-pooling layers, and 2 fully connected layers. The output layer comprises 3 nodes to recognize the 3 conditions of adenocarcinoma (AIS, MIA, and IVA) or 2 nodes for 2 conditions (AIS and MIA/IVA). Results from DL and the 3 radiologists were statistically compared.No significant differences in pathological diagnostic accuracy rates were seen between DL and the 3 radiologists (P >.11). Receiver operating characteristic analysis demonstrated that area under the curve for DL (0.712) was almost the same as that for the radiologist with extensive experience (0.714; P = .98). Compared with the consensus results from radiologists, DL offered significantly inferior sensitivity (P = .0005), but significantly superior specificity (P = .02).Despite the small training data set, diagnostic performance of DL was almost the same as the radiologist with extensive experience. In particular, DL provided higher specificity than radiologists.

    DOI: 10.1097/MD.0000000000016119

  • Invited Article: Label-free nerve imaging with a coherent anti-Stokes Raman scattering rigid endoscope using two optical fibers for laser delivery Reviewed International journal

    Hirose, K., Fukushima, S., Furukawa, T., Niioka, H., Hashimoto, M.

    APL Photonics   3 ( 9 )   092407-1 - 092407-8   2018.9

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    A coherent anti-Stokes Raman scattering (CARS) rigid endoscope using two optical fibers to deliver excitation beams individually is developed. The use of two optical fibers allows the correction of longitudinal chromatic aberration and enhances the CARS signal by a factor of 2.59. The endoscope is used to image rat sciatic nerves with an imaging time of 10 s. Imaging of the rabbit prostatic fascia without sample slicing is also demonstrated, which reveals the potential for the application of the CARS endoscope to robot-assisted surgery.<br />

    DOI: 10.1063/1.5031817

  • Graphical classification of DNA sequences of HLA alleles by deep learning Reviewed

    Jun Miyake, Yuhei Kaneshita, Satoshi Asatani, Seiichi Tagawa, Hirohiko Niioka, Takashi Hirano

    Human Cell   31 ( 2 )   102 - 105   2018.4

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    Alleles of human leukocyte antigen (HLA)-A DNAs are classified and expressed graphically by using artificial intelligence “Deep Learning (Stacked autoencoder)”. Nucleotide sequence data corresponding to the length of 822 bp, collected from the Immuno Polymorphism Database, were compressed to 2-dimensional representation and were plotted. Profiles of the two-dimensional plots indicate that the alleles can be classified as clusters are formed. The two-dimensional plot of HLA-A DNAs gives a clear outlook for characterizing the various alleles.

    DOI: 10.1007/s13577-017-0194-6

  • Coherent anti-stokes Raman scattering rigid endoscope toward robot-assisted surgery Reviewed

    K. Hirose, T. Aoki, T. Furukawa, S. Fukushima, H. Niioka, S. Deguchi, M. Hashimoto

    Biomedical Optics Express   9 ( 2 )   387 - 396   2018.2

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    Label-free visualization of nerves and nervous plexuses will improve the preservation of neurological functions in nerve-sparing robot-assisted surgery. We have developed a coherent anti-Stokes Raman scattering (CARS) rigid endoscope to distinguish nerves from other tissues during surgery. The developed endoscope, which has a tube with a diameter of 12 mm and a length of 270 mm, achieved 0.91% image distortion and 8.6% non-uniformity of CARS intensity in the whole field of view (650 µm diameter). We demonstrated CARS imaging of a rat sciatic nerve and visualization of the fine structure of nerve fibers.

    DOI: 10.1364/BOE.9.000387

  • Classification of C2C12 cells at differentiation by convolutional neural network of deep learning using phase contrast images Reviewed

    Hirohiko Niioka, Satoshi Asatani, Aina Yoshimura, Hironori Ohigashi, Seiichi Tagawa, Jun Miyake

    Human Cell   31 ( 1 )   87 - 93   2018.1

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    In the field of regenerative medicine, tremendous numbers of cells are necessary for tissue/organ regeneration. Today automatic cell-culturing system has been developed. The next step is constructing a non-invasive method to monitor the conditions of cells automatically. As an image analysis method, convolutional neural network (CNN), one of the deep learning method, is approaching human recognition level. We constructed and applied the CNN algorithm for automatic cellular differentiation recognition of myogenic C2C12 cell line. Phase-contrast images of cultured C2C12 are prepared as input dataset. In differentiation process from myoblasts to myotubes, cellular morphology changes from round shape to elongated tubular shape due to fusion of the cells. CNN abstract the features of the shape of the cells and classify the cells depending on the culturing days from when differentiation is induced. Changes in cellular shape depending on the number of days of culture (Day 0, Day 3, Day 6) are classified with 91.3% accuracy. Image analysis with CNN has a potential to realize regenerative medicine industry.

    DOI: 10.1007/s13577-017-0191-9

  • Measurement of DNA Length Changes Upon CpG Hypermethylation by Microfluidic Molecular Stretching. Reviewed International journal

    Daisuke Onoshima, Naoko Kawakita, Daiki Takeshita, Hirohiko Niioka, Hiroshi Yukawa, Jun Miyake, Yoshinobu Baba

    Cell medicine   9 ( 1-2 )   61 - 66   2017.1

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    Abnormal DNA methylation in CpG-rich promoters is recognized as a distinct molecular feature of precursor lesions to cancer. Such unintended methylation can occur during in vitro differentiation of stem cells. It takes place in a subset of genes during the differentiation or expansion of stem cell derivatives under general culture conditions, which may need to be monitored in future cell transplantation studies. Here we demonstrate a microfluidic device for investigating morphological length changes in DNA methylation. Arrayed polymer chains of single DNA molecules were fluorescently observed by parallel trapping and stretching in the microfluidic channel. This observational study revealed that the shortened DNA length is due to the increased rigidity of the methylated DNA molecule. The trapping rate of the device for DNA molecules was substantially unaffected by changes in the CpG methylation.

    DOI: 10.3727/215517916X693087

  • Enhancement of Near-infrared Luminescence of Y2O3:Ln, Yb (Ln = Tm, Ho, Er) by Li-ion Doping for Cellular Bioimaging Reviewed

    Hirohiko Niioka, Jumpei Yamasaki, Doan Thi Kim Dung, Jun Miyake

    CHEMISTRY LETTERS   45 ( 12 )   1406 - 1408   2016.12

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    Bioimaging probes, which can emit near-infrared (NIR) light and are excitable with NIR light, are promising for deep tissue imaging in vivo. Lanthanide-doped phosphors, such as Y2O3:Tm,Yb; Y2O3:Ho,Yb; and Y2O3:Er,Yb, are candidates for the probes. We enhanced the NIR emission of the three kinds of lanthanide-doped phosphor by using Li-ion doping. The probes were applied to cellular imaging.

    DOI: 10.1246/cl.160754

  • Multispectral Emissions of Lanthanide-Doped Gadolinium Oxide Nanophosphors for Cathodoluminescence and Near-Infrared Upconversion/Downconversion Imaging Reviewed

    Doan Thi Kim Dung, Shoichiro Fukushima, Taichi Furukawa, Hirohiko Niioka, Takumi Sannomiya, Kaori Kobayashi, Hiroshi Yukawa, Yoshinobu Baba, Mamoru Hashimoto, Jun Miyake

    NANOMATERIALS   6 ( 9 )   2016.9

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    Comprehensive imaging of a biological individual can be achieved by utilizing the variation in spatial resolution, the scale of cathodoluminescence (CL), and near-infrared (NIR), as favored by imaging probe Gd2O3 co-doped lanthanide nanophosphors (NPPs). A series of Gd2O3:Ln(3+)/Yb3+ (Ln(3+): Tm3+, Ho3+, Er3+) NPPs with multispectral emission are prepared by the sol-gel method. The NPPs show a wide range of emissions spanning from the visible to the NIR region under 980 nm excitation. The dependence of the upconverting (UC)/downconverting (DC) emission intensity on the dopant ratio is investigated. The optimum ratios of dopants obtained for emissions in the NIR regions at 810 nm, 1200 nm, and 1530 nm are applied to produce nanoparticles by the homogeneous precipitation (HP) method. The nanoparticles produced from the HP method are used to investigate the dual NIR and CL imaging modalities. The results indicate the possibility of using Gd2O3 co-doped Ln(3+)/Yb3+ (Ln(3+): Tm3+, Ho3+, Er3+) in correlation with NIR and CL imaging. The use of Gd2O3 promises an extension of the object dimension to the whole-body level by employing magnetic resonance imaging (MRI).

    DOI: 10.3390/nano6090163

  • Correlative near-infrared light and cathodoluminescence microscopy using Y2O3:Ln, Yb (Ln = Tm, Er) nanophosphors for multiscale, multicolour bioimaging Reviewed

    S. Fukushima, T. Furukawa, H. Niioka, M. Ichimiya, T. Sannomiya, N. Tanaka, D. Onoshima, H. Yukawa, Y. Baba, M. Ashida, J. Miyake, T. Araki, M. Hashimoto

    SCIENTIFIC REPORTS   6   2016.5

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    This paper presents a new correlative bioimaging technique using Y2O3:Tm, Yb and Y2O3:Er, Yb nanophosphors (NPs) as imaging probes that emit luminescence excited by both near-infrared (NIR) light and an electron beam. Under 980 nm NIR light irradiation, the Y2O3:Tm, Yb and Y2O3:Er, Yb NPs emitted NIR luminescence (NIRL) around 810 nm and 1530 nm, respectively, and cathodoluminescence at 455 nm and 660 nm under excitation of accelerated electrons, respectively. Multimodalities of the NPs were confirmed in correlative NIRL/CL imaging and their locations were visualized at the same observation area in both NIRL and CL images. Using CL microscopy, the NPs were visualized at the single-particle level and with multicolour. Multiscale NIRL/CL bioimaging was demonstrated through in vivo and in vitro NIRL deep-tissue observations, cellular NIRL imaging, and high-spatial resolution CL imaging of the NPs inside cells. The location of a cell sheet transplanted onto the back muscle fascia of a hairy rat was visualized through NIRL imaging of the Y2O3:Er, Yb NPs. Accurate positions of cells through the thickness (1.5 mm) of a tissue phantom were detected by NIRL from the Y2O3:Tm, Yb NPs. Further, locations of the two types of NPs inside cells were observed using CL microscopy.

    DOI: 10.1038/srep25950

  • Synthesis of Y2O3 nanophosphors by homogeneous precipitation method using excessive urea for cathodoluminescence and upconversion luminescence bioimaging Reviewed

    Shoichiro Fukushima, Taichi Furukawa, Hirohiko Niioka, Masayoshi Ichimiya, Takumi Sannomiya, Jun Miyake, Masaaki Ashida, Tsutomu Araki, Mamoru Hashimoto

    OPTICAL MATERIALS EXPRESS   6 ( 3 )   831 - 843   2016.3

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    Yttrium oxide-based nanophosphors that emit both upconversion luminescence (UPL) and cathodoluminescence (CL) were synthesized by a precipitation method using excessive urea. Precursors of Y2O3 nanophosphors were synthesized with size control to less than 50 nm and a chemical yield greater than 90%. Concentrations of rare-earth co-dopants in nanophosphors were controlled with optimal molar ratios. Co-dopants Tm, Yb/Er, Yb enabled NPs to emit UPL at wavelengths around 810/660 nm and CL at wavelengths around 450/660 nm via excitation with 980 nm NIR light and an electron beam. Synthesized NPs were imaged by NIR and CL microscopy. (C) 2016 Optical Society of America

    DOI: 10.1364/OME.6.000831

  • High-sensitivity and high-spatial-resolution imaging of self-assembled monolayer on platinum using radially polarized beam excited second-harmonic-generation microscopy Reviewed

    Mamoru Hashimoto, Hirohiko Niioka, Koichiro Ashida, Keisuke Yoshiki, Tsutomu Araki

    APPLIED PHYSICS EXPRESS   8 ( 11 )   2015.11

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    High-sensitivity, high-spatial-resolution imaging of organic monolayers on platinum with second harmonic generation (SHG) microscopy using radially polarized beam excitation is investigated. A tightly focused, radially polarized beam forms a longitudinal electric field at the focus. The longitudinal field is enhanced at a metal surface and increases the intensity of SHG from the molecules on the metal surface. The SHG signal from a self-assembled monolayer (SAM) on a platinum surface excited by a radially polarized beam is approximately 3.7 times higher than that obtained with a linearly polarized beam. Improved spatial resolution is also demonstrated using a SAM patterned by electron beam lithography. (C) 2015 The Japan Society of Applied Physics

    DOI: 10.7567/APEX.8.112401

  • Rare-earth-doped nanophosphors for multicolor cathodoluminescence nanobioimaging using scanning transmission electron microscopy Reviewed

    Taichi Furukawa, Shoichiro Fukushima, Hirohiko Niioka, Naoki Yamamoto, Jun Miyake, Tsutomu Araki, Mamoru Hashimoto

    JOURNAL OF BIOMEDICAL OPTICS   20 ( 5 )   2015.5

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    We describe rare-earth-doped nanophosphors (RE-NPs) for biological imaging using cathodoluminescence (CL) microscopy based on scanning transmission electron microscopy (STEM). We report the first demonstration of multicolor CL nanobioimaging using STEM with nanophosphors. The CL spectra of the synthesized nanophosphors (Y2O3:Eu, Y2O3:Tb) were sufficiently narrow to be distinguished. From CL images of RE-NPs on an elastic carbon-coated copper grid, the spatial resolution was beyond the diffraction limit of light. Y2O3:Tb and Y2O3:Eu RE-NPs showed a remarkable resistance against electron beam exposure even at high acceleration voltage (80 kV) and retained a CL intensity of more than 97% compared with the initial intensity for 1 min. In biological CL imaging with STEM, heavy-metal-stained cell sections containing the RE-NPs were prepared, and both the CL images of RE-NPs and cellular structures, such as mitochondria, were clearly observed from STEM images with high contrast. The cellular CL imaging using RE-NPs also had high spatial resolution even though heavy-metal-stained cells are normally regarded as highly scattering media. Moreover, since the RE-NPs exhibit photoluminescence (PL) excited by UV light, they are useful for multimodal correlative imaging using CL and PL. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

    DOI: 10.1117/1.JBO.20.5.056007

  • Y2O3:Tm,Yb nanophosphors for correlative upconversion luminescence and cathodoluminescence imaging Reviewed

    Shoichiro Fukushima, Taichi Furukawa, Hirohiko Niioka, Masayoshi Ichimiya, Jun Miyake, Masaaki Ashida, Tsutomu Araki, Mamoru Hashimoto

    MICRON   67   90 - 95   2014.12

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    We present a phosphor nanoparticle that shows both upconversion luminescence (UCL) and cathodoluminescence (CL). With this particle, low-autofluorescence, deep-tissue and wide-field fluorescence imaging can be achieved with nanometer-order high-spatial-resolution imaging. We synthesized Y2O3:Tm,Yb nanophosphors that emit visible and near-infrared UCL under 980 nm irradiation and blue CL via electron beam excitation. The phosphors were applied to fluorescent imaging of HeLa cells. The photostability of the phosphors was superior to that of a conventional organic dye. We show that after uptake by HeLa cells, the particles can be imaged with SEM and CL contrast in a cellular section. This indicates that correlative UCL and CL imaging of biological samples could be realized. (C) 2014 Elsevier Ltd. All rights reserved.

    DOI: 10.1016/j.micron.2014.07.002

  • Laser-targeted photofabrication of gold nanoparticles inside cells Reviewed

    Nicholas I. Smith, Kentaro Mochizuki, Hirohiko Niioka, Satoshi Ichikawa, Nicolas Pavillon, Alison J. Hobro, Jun Ando, Katsumasa Fujita, Yutaro Kumagai

    NATURE COMMUNICATIONS   5   2014.10

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    Nanoparticle manipulation is of increasing interest, since they can report single molecule-level measurements of the cellular environment. Until now, however, intracellular nanoparticle locations have been essentially uncontrollable. Here we show that by infusing a gold ion solution, focused laser light-induced photoreduction allows in situ fabrication of gold nanoparticles at precise locations. The resulting particles are pure gold nanocrystals, distributed throughout the laser focus at sizes ranging from 2 to 20 nm, and remain in place even after removing the gold solution. We demonstrate the spatial control by scanning a laser beam to write characters in gold inside a cell. Plasmonically enhanced molecular signals could be detected from nanoparticles, allowing their use as nano-chemical probes at targeted locations inside the cell, with intracellular molecular feedback. Such light-based control of the intracellular particle generation reaction also offers avenues for in situ plasmonic device creation in organic targets, and may eventually link optical and electron microscopy.

    DOI: 10.1038/ncomms6144

  • High-resolution microscopy for biological specimens via cathodoluminescence of Eu- and Zn-doped Y2O3 nanophosphors Reviewed

    Taichi Furukawa, Hirohiko Niioka, Masayoshi Ichimiya, Tomohiro Nagata, Masaaki Ashida, Tsutomu Araki, Mamoru Hashimoto

    Optics Express   21 ( 22 )   25655 - 25663   2013.11

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    High-resolution microscopy for biological specimens was performed using cathodoluminescence (CL) of Y2O3:Eu, Zn nanophosphors, which have high CL intensity due to the incorporation of Zn. The intensity of Y2O3:Eu nanophosphors at low acceleration voltage (3 kV) was increased by adding Zn. The CL intensity was high enough for imaging even with a phosphor size as small as about 30 nm. The results show the possibility of using CL microscopy for biological specimens at single-protein-scale resolution. CL imaging of HeLa cells containing laserablated Y2O 3:Eu, Zn nanophosphors achieved a spatial resolution of a few tens of nanometers. Y2O3:Eu, Zn nanophosphors in HeLa cells were also imaged with 254 nm ultraviolet light excitation. The results suggest that correlative microscopy using CL, secondary electrons and fluorescence imaging could enable multi-scale investigation of molecular localization from the nanoscale to the microscale. ©2013 Optical Society of America.

    DOI: 10.1364/OE.21.025655

  • Fast spectral coherent anti-Stokes Raman scattering microscopy with high-speed tunable picosecond laser Reviewed

    Harsono Cahyadi, Junichi Iwatsuka, Takeo Minamikawa, Hirohiko Niioka, Tsutomu Araki, Mamoru Hashimoto

    JOURNAL OF BIOMEDICAL OPTICS   18 ( 9 )   2013.9

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    We develop a coherent anti-Stokes Raman scattering (CARS) microscopy system equipped with a tunable picosecond laser for high-speed wavelength scanning. An acousto-optic tunable filter (AOTF) is integrated in the laser cavity to enable wavelength scanning by varying the radio frequency waves applied to the AOTF crystal. An end mirror attached on a piezoelectric actuator and a pair of parallel plates driven by galvanometer motors are also introduced into the cavity to compensate for changes in the cavity length during wavelength scanning to allow synchronization with another picosecond laser. We demonstrate fast spectral imaging of 3T3-L1 adipocytes every 5 cm(-1) in the Raman spectral region around 2850 cm(-1) with an image acquisition time of 120 ms. We also demonstrate fast switching of Raman shifts between 2100 and 2850 cm(-1), corresponding to CD2 symmetric stretching and CH2 symmetric stretching vibrations, respectively. The fast-switching CARS images reveal different locations of recrystallized deuterated and nondeuterated stearic acid. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

    DOI: 10.1117/1.JBO.18.9.096009

  • Molecular Orientation Imaging of Liquid Crystals by Tunable-Polarization-Mode Coherent Anti-Stokes Raman Scattering Microscopy Reviewed

    Takeo Minamikawa, Tatsuro Takagi, Hirohiko Niioka, Makoto Kurihara, Nobuyuki Hashimoto, Tsutomu Araki, Mamoru Hashimoto

    APPLIED PHYSICS EXPRESS   6 ( 7 )   2013.7

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    We have developed a tunable-polarization-mode coherent anti-Stokes Raman scattering (CARS) microscope with compact polarization mode converters constructed using eight-segmented liquid-crystal spatial light modulators. The polarization modes, such as linear, radial, and azimuthal polarizations, of two excitation beams are controlled independently and are switched without any mechanical tuning in less than 300 ms. We use the system to detect the molecular orientation of 4-cyano-4'-octylbiphenyl (8CB) liquid crystals aligned parallel and perpendicular to the optical axis. We also observe CARS images of liquid crystal defects known as focal conic domains, demonstrating the potential of our molecular orientation imaging system. (C) 2013 The Japan Society of Applied Physics

    DOI: 10.7567/APEX.6.072401

  • Formation of a carbon nanoribbon by spontaneous collapse of a carbon nanotube grown from a γ-Fe nanoparticle via an origami mechanism Reviewed

    Hideo Kohno, Takuya Komine, Takayuki Hasegawa, Hirohiko Niioka, Satoshi Ichikawa

    Nanoscale   5 ( 2 )   570 - 573   2013.1

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    Formation of a carbon nanoribbon by spontaneous collapse of a carbon nanotube grown from a γ-Fe nanoparticle via an origami mechanism
    We report a simple method of fabricating graphite nanoribbons by utilizing a self-collapsing mechanism of multi-walled carbon nanotubes during their growth. In the growth process, a nanotube is expelled from a γ-Fe seed nanoparticle, and then collapses spontaneously forming a nanoribbon. Our microscopic analysis of the structures and crystal orientations of γ-Fe nanoparticles and graphite nanoribbons suggests a possible mechanism of the collapse of nanotubes into nanoribbons, an origami mechanism. Our approach can be developed toward the fabrication of bi-layered graphene nanoribbons. Furthermore, the origami mechanism also yields graphitic nano-tetrahedrons. © The Royal Society of Chemistry.

    DOI: 10.1039/c2nr32607h

  • A Time-Resolved CMOS Image Sensor With Draining-Only Modulation Pixels for Fluorescence Lifetime Imaging Reviewed

    Zhuo Li, Shoji Kawahito, Keita Yasutomi, Keiichiro Kagawa, Juichiro Ukon, Mamoru Hashimoto, Hirohiko Niioka

    IEEE TRANSACTIONS ON ELECTRON DEVICES   59 ( 10 )   2715 - 2722   2012.10

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    This paper presents a time-resolved CMOS image sensor with draining-only modulation (DOM) pixels, for time-domain fluorescence lifetime imaging. In the DOM pixels using a pinned photodiode (PPD) technology, a time-windowed signal charge transfer from a PPD to a pinned storage diode (PSD) is controlled by a draining gate only, without a transfer gate between the two diodes. This structure allows a potential barrierless and trapless charge transfer from the PPD to the PSD. A 256 x 256 pixel time-resolved CMOS imager with 7.5 x 7.5 mu m(2) DOM pixels has been implemented using 0.18-mu m CMOS image sensor process technology with PPD option. The prototype demonstrates high sensitivity for weak signal of less than one electron per light pulse and accurate measurement of fluorescence decay process with subnanosecond time resolution.

    DOI: 10.1109/TED.2012.2209179

  • Multicolor Cathodoluminescence Microscopy for Biological Imaging with Nanophosphors Reviewed

    Hirohiko Niioka, Taichi Furukawa, Masayoshi Ichimiya, Masaaki Ashida, Tsutomu Araki, Mamoru Hashimoto

    APPLIED PHYSICS EXPRESS   4 ( 11 )   2011.11

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    We report the first demonstration of a multicolor high-spatial-resolution imaging technique for observation of biological cells using cathodoluminescence from nanophosphors. Three kinds of rare-earth-doped nanophosphors were injected into J744A.1 macrophages, and the spatial distribution of nanophosphors was visualized by using a scanning electron microscope cathodoluminescence (SEM-CL) system. The spectral bandwidth of the phosphors was narrow enough to distinguish the types of the phosphors. CL images of the nanophosphors on Si substrates were obtained with high resolution comparable to that of SEM images. These nanophosphors will be candidates to image more than two kinds of biological molecules at high resolution. (C) 2011 The Japan Society of Applied Physics

    DOI: 10.1143/APEX.4.112402

  • Real-time imaging of laser-induced membrane disruption of a living cell observed with multifocus coherent anti-Stokes Raman scattering microscopy Reviewed

    Takeo Minamikawa, Hirohiko Niioka, Tsutomu Araki, Mamoru Hashimoto

    JOURNAL OF BIOMEDICAL OPTICS   16 ( 2 )   2011.2

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    We demonstrate the real-time imaging of laser-induced disruption of the cellular membrane in a living HeLa cell and its cellular response with a multifocus coherent anti-Stokes Raman scattering (CARS) microscope. A near-infrared pulsed laser beam tightly focused on the cellular membrane of a living cell induces ablation at the focal point causing a local disruption of the cellular membrane. After the membrane disruption a dark spot decreasing CARS intensity of 2840 cm(-1) Raman shift at the disrupted site appears. This dark spot immediately disappears and a strong CARS signal is observed around the disrupted site. This increase of the CARS signal might be caused by resealing of the disrupted site via aggregation of the patch lipid vesicles in the cytoplasm. The accumulation of lipids around the disrupted site is also confirmed with three-dimensional CARS images of a cell before and after membrane disruption. The temporal behavior of the CARS signal at the disrupted site is observed to detect the fusion dynamics of patch vesicles. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI:10.1117/1.3533314]

    DOI: 10.1117/1.3533314

  • Graphene/Graphite-Coated SiC Nanowires Grown by Metal-Organic Chemical Vapor Deposition in One Step Reviewed

    Hideo Kohno, Kazuki Yagi, Hirohiko Niioka

    JAPANESE JOURNAL OF APPLIED PHYSICS   50 ( 1 )   2011.1

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    Graphene/graphite-coated SiC nanowires are fabricated from diethylsilane or divinyldimethylsilane by Fe-assisted metal-organic chemical vapor deposition. When diethylsilane is used, a few layers of graphene are formed, while 30-40-nm-thick graphite is formed from divinyldimethylsilane. (C) 2011 The Japan Society of Applied Physics

    DOI: 10.1143/JJAP.50.018001

  • Nanocommunication Design in Graduate-Level Education and Research Training Reviewed

    Hirohiko Niioka

    J. Korean Vacuum Society   19 ( 6 )   423 - 431   2010.11

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    DOI: 10.5757/jkvs.2010.19.6.423

  • Femtosecond laser nano-ablation in fixed and non-fixed cultured cells Reviewed

    H. Niioka, N. I. Smith, K. Fujita, Y. Inouye, S. Kawata

    OPTICS EXPRESS   16 ( 19 )   14476 - 14495   2008.9

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    Language:English   Publishing type:Research paper (scientific journal)  

    To understand the onset and morphology of femtosecond laser submicron ablation in cells and to study physical evidence of intracellular laser irradiation, we used transmission electron microscopy (TEM). The use of partial fixation before laser irradiation provides for clear images of sub-micron intracellular laser ablation, and we observed clear evidence of bubble-type physical changes induced by femtosecond laser irradiation at pulse energies as low as 0.48 nJ in the nucleus and cytoplasm. By taking ultrathin sliced sections, we reconstructed the laser affected subcellular region, and found it to be comparable to the point spread function of the laser irradiation. Laser-induced bubbles were observed to be confined by the surrounding intracellular structure, and bubbles were only observed with the use of partial pre-fixation. Without partial pre-fixation, laser irradiation of the nucleus was found to produce observable aggregation of nanoscale electron dense material, while irradiation of cytosolic regions produced swollen mitochondria but residual local physical effects were not observed. This was attributed to the rapid collapse of bubbles and/or the diffusion of any observable physical effects from the irradiation site following the laser exposure. (c) 2008 Optical Society of America.

    DOI: 10.1364/OE.16.014476

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Presentations

  • 深層学習を用いた画像データ解析技術とその医療応用について Invited

    新岡宏彦

    第101回日本生理学会大会  2024.3 

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    Event date: 2024.3

    Language:Japanese  

    Venue:北九州国際会議場 及び西日本総合展示場   Country:Japan  

  • データ解析コンテストを通じたDX人材育成 Invited

    新岡宏彦

    医情工連携シンポジウム - バイオDX人材はどこにいる?  2023.12 

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    Event date: 2023.12

    Language:Japanese  

    Venue:大阪大学 銀杏会館 阪急電鉄・三和銀行ホール   Country:Japan  

    バイオDX人材へのニーズが社会的に高まっており、医情工の連携による取り組みが求められています。
    そこで、「阪大内において、どのようなニーズがあるのか?」「養成の取り組みがあるのか?」
    「バイオDX人材はどのように養成されたのか?」を俯瞰するシンポジウムを開催します。

  • 近年の深層学習技術と医療画像データへの応用 Invited

    新岡宏彦

    第 33 回日本心血管画像動態学会  2023.1 

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    Event date: 2023.1

    Language:Japanese  

    Venue:岡山コンベンションセンター   Country:Japan  

  • 深層学習の基礎と医療応用例のご紹介と独学する方法について Invited

    新岡宏彦

    第 33 回日本心血管画像動態学会  2023.1 

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    Event date: 2023.1

    Language:Japanese  

    Venue:岡山コンベンションセンター   Country:Japan  

    教育講演

  • 自己教師あり学習を用いた甲状腺細胞診画像の特徴表現獲得と画像分類応用

    安部 政俊, 廣川 満良, 鈴木 彩菜, 長原 一, 宮内 昭, 赤水 尚史, 新岡 宏彦

    バイオイメージング  2022.8 

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    Event date: 2022.8

    Language:Japanese  

    Country:Other  

  • 深層学習 AI を用いた医療画像解析とイメージング装置開発 Invited

    新岡宏彦

    第63回日本臨床細胞学会総会  2022.6 

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    Event date: 2022.6

    Language:Japanese  

    Country:Other  

  • Near real-time nerve visualization using coherent Raman scattering rigid endoscope and deep learning-based image processing for nerve-sparing surgery

    Naoki Yamato, Hirohiko Niioka, Jun Miyake, Mamoru Hashimoto

    Biomedical Vibrational Spectroscopy 2022: Advances in Research and Industry  2022.3 

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    Event date: 2022.3

    Language:Others  

    Country:Other  

  • 医用画像診断支援のための人工知能プログラム開発/研究 Invited

    新岡宏彦

    異分野融合型研究開発推進支援事業シンポジウム  2022.1 

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    Event date: 2022.1

    Language:Japanese  

    Country:Other  

  • 画像診断におけるArtificial Intelligenceの臨床応用 食道癌リンパ節転移診断能に関する検討

    林 芳矩, 新岡 宏彦, 牧野 知紀, 兼子 晃寛, 小林 照之, 梁川 雅弘, 長原 一, 三宅 淳, 富山 憲幸, 江口 英利, 土岐 祐一郎

    日本臨床外科学会雑誌  2021.10 

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    Event date: 2021.10

    Language:Japanese  

    Country:Other  

  • 医療におけるディープラーニング Invited

    新岡宏彦

    第2回循環器AI研究会 ~医療者のためのゼロからわかるディープラーニング~  2021.9 

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    Event date: 2021.9

    Language:Japanese  

    Country:Other  

  • 学生AIサークルと医療AI人材育成 Invited

    新岡 宏彦

    第3回日本メディカルAI学会学術集会  2021.6 

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    Event date: 2021.6

    Language:Japanese  

    Country:Other  

  • AIを用いた甲状腺細胞診支援システム AI differential diagnosis for cytology of the thyroid (ADDICT)の開発に向けて Invited

    廣川満良, 新岡宏彦, 鈴木彩菜, 安部政俊, 式見彰浩, 長原一, 宮内昭

    第62回日本臨床細胞学会総会春期大会  2021.6 

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    Event date: 2021.6

    Language:Japanese  

    Venue:幕張メッセ国際会議場   Country:Japan  

  • 次世代の甲状腺細胞診 AIを用いた甲状腺細胞診支援システム(AD-DICT)の開発に向けて

    廣川 満良, 新岡 宏彦, 鈴木 彩菜, 安部 政俊, 式見 彰浩, 長原 一, 宮内 昭

    日本臨床細胞学会雑誌  2021.5 

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    Event date: 2021.5

    Language:Japanese  

    Country:Other  

  • Prediction of Coronary Plaque Vulnerability Using OCT Images and Deep Learning Invited

    新岡 宏彦, 三宅 淳, 上村 史朗

    第85回日本循環器学会学術集会  2021.3 

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    Event date: 2021.3

    Language:English  

    Country:Other  

    Prediction of Coronary Plaque Vulnerability Using OCT Images and Deep Learning

  • Artificial IntelligenceによるCT画像を用いた食道癌リンパ節転移診断能の検討

    小林 照之, 新岡 宏彦, 牧野 知紀, 山崎 誠, 山崎 翔平, 梁川 雅弘, 長原 一, 三宅 淳, 江口 英利, 土岐 祐一郎

    日本食道学会学術集会プログラム・抄録集  2020.12 

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    Event date: 2020.12

    Language:Japanese  

    Country:Other  

  • Artificial IntelligenceによるCT画像を用いた食道癌リンパ節転移診断能の検討

    林 芳矩, 新岡 宏彦, 牧野 知紀, 小林 照之, 山崎 翔平, 梁川 雅弘, 山崎 誠, 長原 一, 三宅 淳, 富山 憲幸, 江口 英利, 土岐 祐一郎

    日本臨床外科学会雑誌  2020.10 

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    Event date: 2020.10

    Language:Japanese  

    Country:Other  

  • 循環器疾患のAI画像診断 機械学習を用いた心筋病理組織像からの心不全患者の予後予測(Prediction of Prognosis of Patients with Heart Failure Using Machine Learning on Myocardial Histopathological Image)

    土肥 智晴, 新岡 宏彦, 彦惣 俊吾, 板野 景子, 大谷 朋仁, 佐藤 淳哉, 三宅 淳, 坂田 泰史

    日本循環器学会学術集会抄録集  2020.7 

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    Event date: 2020.7

    Language:English  

    Country:Other  

  • 非線形ラマン散乱硬性内視鏡と深層学習による神経イメージング Invited

    大和 尚記, 松谷 真奈, 工藤 信樹, 新岡 宏彦, 三宅 淳, 橋本 守

    第32回日本内視鏡外科学会総会 

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    Event date: 2019.12

    Language:Japanese  

    Venue:パシフィコ横浜   Country:Japan  

  • Nerve imaging and segmentation used by coherent Raman endoscopy and deep learning Invited International conference

    M. Hashimoto, N. Yamato, M. Matsuya, H. Niioka, J. Miyake

    Biomedical Raman Imaging 2019 

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    Event date: 2019.11

    Language:English  

    Venue:Ichokaikan, Osaka University, Japan   Country:Japan  

  • ディープラーニングとバイオメディカルイメージング技術 Invited

    新岡 宏彦

    第71回日本生物工学会大会 

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    Event date: 2019.9

    Language:Japanese  

    Venue:岡山大学島津キャンパス   Country:Japan  

  • Bio-Medical Optical Imaging Using Deep Learning Invited International conference

    Hirohiko Niioka

    US-Japan Workshop on Bioengineering and Information Science 

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    Event date: 2019.9

    Language:English  

    Venue:University of California, San Diego, USA (Online)   Country:United States  

    Bio-Medical Optical Imaging Using Deep Learning

  • Bio-Medical imaging supported by deep learning Invited International conference

    Hirohiko Niioka

    International Workshop on Symbolic-Neural Learning (SNL-2019) 

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    Event date: 2019.7

    Language:English  

    Venue:Odaiba Miraikan, Tokyo, Japan   Country:Japan  

    Bio-Medical imaging supported by deep learning

  • Deep learningによるCT画像を用いた食道癌リンパ節転移診断能の検討

    小林 照之, 牧野 知紀, 新岡 宏彦, 山崎 誠, 田中 晃司, 梁川 雅弘, 長原 一, 三宅 淳, 森 正樹, 土岐 祐一郎

    日本消化器外科学会総会  2019.7 

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    Event date: 2019.7

    Language:Japanese  

    Country:Other  

  • AIの医療画像応用と医療用光イメージング機器開発 Invited

    新岡 宏彦

    第58回 日本生体医工学会大会 

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    Event date: 2019.6

    Language:Japanese  

    Venue:沖縄コンベンションセンター   Country:Japan  

  • Artificial Intelligenceを用いた食道癌右反回神経リンパ節のCT転移診断能の検討

    小林 照之, 新岡 宏彦, 牧野 知紀, 山崎 誠, 田中 晃司, 梁川 雅弘, 長原 一, 三宅 淳, 森 正樹, 土岐 祐一郎

    日本食道学会学術集会プログラム・抄録集  2019.6 

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    Event date: 2019.6

    Language:Japanese  

    Country:Other  

  • 深層学習によるバイオ・メディカル画像データの解析 Invited

    新岡 宏彦

    第16回 医用分光学研究会 

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    Event date: 2018.11

    Language:Japanese  

    Venue:北海道大学 フロンティア応用化学研究棟   Country:Japan  

  • コヒーレントアンチストークスラマン散乱硬性鏡の開発と神経イメージングへの応用 Invited

    橋本 守, 大和 尚記, 新岡 宏彦

    第16回 医用分光学研究会 

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    Event date: 2018.11

    Language:Japanese  

    Venue:北海道大学 フロンティア応用化学研究棟   Country:Japan  

  • 深層学習とバイオメディカル画像データへの応用 Invited

    新岡 宏彦

    第49回中化連秋季大会 

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    Event date: 2018.11

    Language:Others  

    Venue:名古屋大学工学研究科   Country:Japan  

  • Development of nanophosphors for dual-modal cellular imaging with cathodoluminescence microscope and near-infrared light microscope Invited

    新岡 宏彦

    公益社団法人日本顕微鏡学会第61回シンポジウム -新時代へと深化する顕微鏡学 Microscopy Advancing to New Frontier- 

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    Event date: 2018.11

    Language:Japanese  

    Venue:富山国際会議場   Country:Japan  

  • Deep Learningのバイオ・医療画像応用 Invited

    新岡 宏彦

    平成30年度統計数理研究所共同研究集会 生体信号・イメージングデータ解析に基づく医療・健康データ科学の展開 

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    Event date: 2018.10

    Language:Japanese  

    Venue:統計数理研究所   Country:Japan  

  • 特別企画 若手1 研究格差社会をどう生きるか Invited

    新岡 宏彦

    第77回日本癌学会学術総会 

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    Event date: 2018.9

    Language:Japanese  

    Venue:大阪国際会議場 リーガロイヤルホテル大阪   Country:Japan  

  • 深層学習によるバイオメディカルデータ解析 Invited

    新岡 宏彦

    第57回日本生体医工学会大会 

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    Event date: 2018.6

    Language:Japanese  

    Venue:札幌コンベンションセンター   Country:Japan  

  • 再生医療応用を目指した近赤外光深部イメージング用蛍光体の開発

    新岡 宏彦, 福島 昌一郎, 橋本 守, 荒木 勉, 小野島 大介, 湯川 博, 馬場 嘉信, 三宅 淳

    日本生物工学会大会講演要旨集  2014.8 

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    Event date: 2014.8

    Language:Japanese  

    Country:Other  

  • Rare-earth doped Y2O3 nanophosphors for biological cathodoluminescence imaging Invited International conference

    H. Niioka, T. Furukawa, S. Fukushima, M. Ichimiya, J. Miyake, M. Ashida, T. Araki, M. Hashimoto

    International Conference on Small Science 

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    Event date: 2013.12

    Language:English  

    Venue:Las Vegas, USA   Country:United States  

    Rare-earth doped Y2O3 nanophosphors for biological cathodoluminescence imaging

  • Correlative cathodoluminescence and fluorescence biological imaging (応用物理学会論文奨励賞受賞記念講演) Invited

    新岡 宏彦

    第74回応用物理学会秋季学術講演会 

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    Event date: 2013.9

    Language:Japanese  

    Venue:同志社大学京田辺キャンパス   Country:Japan  

  • 希土類添加ナノ蛍光体粒子を用いた蛍光・CL細胞イメージング Invited

    新岡 宏彦, 古川 太一, 一宮 正義, 永田 智啓, 芦田 昌明, 荒木 勉, 橋本 守

    生理研研究会 

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    Event date: 2012.10

    Language:Japanese  

    Venue:生理学研究所   Country:Japan  

  • ナノ蛍光体粒子とカソードルミネッセンス顕微鏡を用いたマルチカラー生体イメージング Invited

    新岡 宏彦, 古川 太一, 一宮 正義, 芦田 昌明, 荒木 勉, 橋本 守

    日本顕微鏡学会 

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    Event date: 2012.5

    Language:Japanese  

    Venue:つくば国際会議場   Country:Japan  

  • データ分析コンペを通じた人材育成とweb3.0技術を用いた医療データ流通 Invited

    新岡宏彦

    第83回日本医学放射線学会総会  2024.4 

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    Language:Japanese  

    Venue:パシフィコ横浜   Country:Japan  

  • ディープラーニング を活用した医用画像解析の事例やトピックス Invited

    新岡宏彦

    第2回大阪トップランナー育成事業 定期交流会  2022.12 

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    Language:Japanese  

    Country:Other  

  • 「フォトニクス×AI」~AIを用いた画像処理とその応用について~ Invited

    新岡 宏彦

    第9回 フォトニクスセミナー  2020.12 

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    Language:Japanese  

    Country:Japan  

  • 人工知能がバイオメディカルイメージングを加速する? Invited

    新岡 宏彦

    第11回PhotoBIOワークショップ  2020.9 

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    Language:Japanese  

    Venue:オンライン   Country:Japan  

  • 人工知能とバイオメディカルイメージング機器開発 Invited

    新岡 宏彦

    前臨床FGセミナー2020 「AI、ダイバシティ―、そして医薬」  2020.2 

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    Language:Japanese  

    Venue:立命館大学東京キャンパス   Country:Japan  

  • 深層学習AIを搭載した光イメージング医療機器の開発 Invited

    新岡 宏彦

    AI Optics研究会  2020.5 

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    Language:Japanese  

    Venue:オンライン   Country:Japan  

  • 深層学習の基礎とバイオ・メディカル画像データへの応用 Invited

    新岡 宏彦

    ポストLEDフォトニクス講演会  2020.1 

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    Language:Japanese  

    Venue:徳島大学 ポストLEDフォトニクス研究所   Country:Japan  

  • 人工知能 × 医療画像 × 光イメージング機器開発 Invited

    新岡 宏彦

    MMDS公開講座 医療×AI  2019.10 

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    Language:Japanese  

    Venue:大阪大学基礎工学研究科・基礎工学国際棟   Country:Japan  

  • 人工知能(深層学習)の医療画像データへの応用 Invited

    新岡 宏彦

    関西医科大学内科学第二講座同門会  2019.6 

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    Language:Japanese  

    Venue:リーガロイヤルホテル大阪 タワーウイング2階「桐」   Country:Japan  

  • 人工知能とバイオメディカルイメージング機器開発 Invited

    新岡 宏彦

    バイオグリッド研究会2019「IoT時代のデジタルメディスン」  2019.10 

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    Language:Japanese  

    Venue:グランフロント大阪 タワーC カンファレンスルームC04   Country:Japan  

  • 人工知能を搭載した光イメージング機器の開発 Invited

    新岡 宏彦

    MDF(次世代医療システム産業化フォーラム)第6回医工連携マッチング例会  2019.12 

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    Language:Japanese  

    Venue:大阪産業創造館   Country:Japan  

  • 医療AIの現状と未来 Invited

    新岡 宏彦

    第25回日本心臓リハビリテーション学会学術集会 -行動医学からICTまで-  2019.7 

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    Language:Japanese  

    Venue:大阪国際会議場   Country:Japan  

  • 深層学習と医療応用を目指した光イメージング機器開発 Invited

    新岡 宏彦

    第94回産研テクノサロン  2019.11 

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    Language:Japanese  

    Venue:大阪・梅田 富国生命ビル4F まちラボ A   Country:Japan  

  • Technologies of Deep Learning for Medical Applications Invited International conference

    Hirohiko Niioka

    The 9th MEI3 Center International Symposium -AI Medicine: Revolution-  2018.3 

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    Language:English  

    Venue:Icho Kaikan 3F Hall, Osaka University, Osaka, Japan   Country:Japan  

    Technologies of Deep Learning for Medical Applications

  • データサイエンティスト養成の取り組み Invited

    新岡 宏彦

    コンソーシアム関西 第七回 臨床医工情報学連携セミナー  2018.7 

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    Language:Japanese  

    Venue:大阪大学中之島センター   Country:Japan  

  • 医療画像への人工知能技術の応用 Invited

    新岡 宏彦

    第二十一回最先端医療イノベーションセンター 定例セミナー  2018.11 

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    Language:Japanese  

    Venue:大阪大学最先端医療イノベーションセンター   Country:Japan  

  • 深層学習の基礎とバイオメディカルデータへの応用 Invited

    新岡 宏彦

    第398回光ナノサイエンス特別講義  2018.7 

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    Language:Japanese  

    Venue:奈良先端科学技術大学院大学   Country:Japan  

  • ディープラーニングをバイオメディカルに如何に使うか Invited

    新岡 宏彦

    CBI学会2017年大会 データ駆動型研究が拓く創薬  2017.10 

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    Language:Japanese  

    Venue:タワーホール船堀   Country:Japan  

  • ディープラーニングによるバイオデータ解析 Invited

    新岡 宏彦

    大阪大学医学系研究科フォーラム 第8回若手研究フォーラム  2017.2 

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    Language:Japanese  

    Venue:大阪大学吹田キャンパス 銀杏会館 3F 阪急電鉄・三和銀行ホール   Country:Japan  

  • 生体イメージングデータに対する深層学習の応用 Invited

    新岡 宏彦

    平成29年度統計数理研究所共同研究集会 生体信号・イメージングデータ解析に基づくダイナミカルバイオインフォマティクスの展開  2017.10 

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    Venue:統計数理研究所   Country:Japan  

  • 医療画像の解析と応用(幹細胞、ガン細胞、X線画像、MRI等) Invited

    新岡 宏彦

    産学連携・クロスイノベーションイニシアチブ/未来医療交流会/最先端医療イノベーションセンター合同セミナー「AI・ディープラーニング等の現状と医学領域への応用可能性」  2016.12 

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    Venue:大阪大学医学部講義棟1階A講堂   Country:Japan  

  • カソードルミネッセンス顕微鏡と近赤外光学顕微鏡を用いたマルチスケールバイオイメージング Invited

    新岡 宏彦

    異分野融合による新規分離分析法の創成のための若手講演会議  2015.11 

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    Venue:大阪大学 基礎工学研究科   Country:Japan  

  • マルチプレックス四次ラマン顕微鏡の開発と非線形光学結晶観察 Invited

    新岡 宏彦, 橋本 守

    日本分光学会赤外ラマン分光部会  2015.1 

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    Venue:大阪大学基礎工学研究科・基礎工学国際棟   Country:Japan  

  • 生命情報を解析するためのディープラーニングの実装と応用 -プログラミング、コンピューター制作から応用まで- Invited

    浅谷 学嗣, 新岡 宏彦, 三宅 淳

    𣳾地研究室公開セミナー  2015.12 

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    Venue:Qbic 生命システム研究センター 理化学研究所   Country:Japan  

  • Towards molecular imaging in multiscale with using fluorescent nano-probes excited by both NIR light and electron beam Invited International conference

    Hirohiko Niioka, Jun Miyake

    International Symposium on Nanomedicine Molecular Science  2014.1 

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    Venue:Nagoya University, Aichi, Japan   Country:Japan  

    Towards molecular imaging in multiscale with using fluorescent nano-probes excited by both NIR light and electron beam

  • カソードルミネッセンス顕微鏡と光学顕微鏡の融合 Invited

    新岡 宏彦, 古川 太一, 福島 昌一郎, 一宮 正義, 三宅 淳, 芦田 昌明, 荒木 勉, 橋本 守

    顕微鏡学会分科会バイオメディカルニューマイクロスコープ  2014.3 

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    Venue:帝京大学医学部   Country:Japan  

  • ナノ蛍光体を用いた多色カソードルミネッセンス細胞イメージング Invited

    新岡 宏彦, 古川 太一, 一宮 正義, 芦田 昌明, 荒木 勉, 橋本 守

    顕微鏡学会分科会バイオメディカルニューマイクロスコープ  2012.3 

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    Venue:帝京大学医学部   Country:Japan  

  • ナノ蛍光体粒子を用いたマルチカラー生体カソードルミネッセンスイメージング Invited

    新岡 宏彦

    第22回フォトニクスコロキアム  2011.8 

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    Venue:大阪大学フォトニクスセンター   Country:Japan  

  • 自己教師あり学習を用いた甲状腺細胞診画像の特徴表現獲得と画像分類応用

    安部 政俊, 廣川 満良, 鈴木 彩菜, 長原 一, 宮内 昭, 赤水 尚史, 新岡 宏彦

    バイオイメージング  2022.8  日本バイオイメージング学会

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  • 自己教師あり学習と少数教師ラベルを用いた甲状腺細胞診画像分類

    安部 政俊, 廣川 満良, 鈴木 彩菜, 新岡 宏彦

    日本臨床細胞学会雑誌  2023.5  (公社)日本臨床細胞学会

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  • 病理画像を用いたAIモデルによる肝細胞癌の多倍体化予測

    松浦 敬憲, 安部 政俊, 原田 宜幸, 木戸 正浩, 長原 一, 新岡 宏彦, 福本 巧, 上田 佳秀, 原 英二, 児玉 裕三, 松本 知訓

    日本消化器病学会雑誌  2023.10  (一財)日本消化器病学会

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  • 甲状腺細胞診の現状と次世代への挑戦 AIが創る次世代甲状腺細胞診

    鈴木 彩菜, 廣川 満良, 新岡 宏彦, 安部 政俊, 新井 悠介, 長原 一, 宮内 昭

    日本臨床細胞学会雑誌  2022.5  (公社)日本臨床細胞学会

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  • 深紫外励起蛍光顕微鏡を用いたThin-slice-free histology

    中尾 龍太, 新岡 宏彦, 田中 秀央, 高松 哲郎

    日本組織細胞化学会総会・学術集会講演プログラム・予稿集  2022.10  日本組織細胞化学会

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  • 医工情報学に基づく次世代型医学の展開 深層学習を用いた画像データ解析技術とその医療応用(Deployment of the next generation medicine with informatics and engineering Image data analysis and medical applications using deep learning)

    Niioka Hirohiko

    The Journal of Physiological Sciences  2024.5  (一社)日本生理学会

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  • 冠動脈脆弱性プラークの臨床転帰への影響 冠動脈OCT画像を用いた人工知能プログラムによる解析(Impact of Coronary Vulnerable Plaque on Clinical Outcome: Analysis with Artificial Intelligence Program on Coronary OCT Imaging)

    Kume Teruyoshi, Niioka Hirohiko, Yamada Ryotaro, Miyake Jun, Akasaka Takashi, Saito Yoshihiko, Uemura Shiro

    日本循環器学会学術集会抄録集  2023.3  (一社)日本循環器学会

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  • インターベンション領域におけるAI画像診断技術の進歩 冠動脈光干渉断層イメージングのAI深層学習によるプラーク診断と冠動脈イベント予測

    久米 輝善, 新岡 宏彦, 久保 隆史, 添田 恒有, 渡邉 真言, 山田 亮太郎, 坂田 泰史, 宮本 恵宏, 三宅 淳, 赤阪 隆史, 斎藤 能彦, 上村 史朗

    日本心血管インターベンション治療学会抄録集  2022.7  (一社)日本心血管インターベンション治療学会

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  • Thin-slice-free未固定検体画像におけるSematic segmentationを用いた乳癌検出

    松井 智也, 富本 舜将, 中尾 龍太, 小西 英一, 新岡 宏彦, 直居 靖人, 長原 一, 高松 哲郎

    日本病理学会会誌  2024.2  (一社)日本病理学会

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  • Digital Pathology・Cytology/人工知能(AI) 深層学習AIを用いた医療画像解析とイメージング装置開発

    新岡 宏彦

    日本臨床細胞学会雑誌  2022.5  (公社)日本臨床細胞学会

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  • DeepLearningによるヒトES細胞培養過程の予測

    淺野 友良, 筒井 奎剛, 須賀 英隆, 新岡 宏彦, 湯川 博, 有馬 寛

    日本内分泌学会雑誌  2022.7  (一社)日本内分泌学会

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  • DeepLearningによるヒトES細胞培養過程の予測

    淺野 友良, 須賀 英隆, 筒井 奎剛, 湯川 博, 新岡 宏彦, 有馬 寛

    日本内分泌学会雑誌  2023.5  (一社)日本内分泌学会

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  • Deep Learningを利用した多能性幹細胞の分化予測

    淺野 友良, 須賀 英隆, 村上 奏, 湯川 博, 新岡 宏彦, 有馬 寛

    日本内分泌学会雑誌  2024.4  (一社)日本内分泌学会

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  • CycleGANを用いたThin-slice-free組織標本の疑似HE変換

    中尾 龍太, 佐藤 淳哉, 新岡 宏彦, 田中 秀央, 高松 哲郎

    日本病理学会会誌  2023.3  (一社)日本病理学会

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  • AIを用いた消化器疾患の診断・治療への応用 AIを用いた肝細胞癌多倍体化診断モデルの作成とTCGA大規模データを用いた検討

    松浦 敬憲, 上田 佳秀, 安部 政俊, 新岡 宏彦, 長原 一, 小松 昇平, 福本 巧, 児玉 裕三, 松本 知訓

    日本消化器病学会雑誌  2024.3  (一財)日本消化器病学会

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MISC

  • STED顕微鏡による細胞組織深部超解像イメージングについて

    新岡 宏彦

    BIO Clinica   37 ( 11 )   1017 - 1021   2022.10   ISSN:0919-8237

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    光の回折限界を超える空間分解能でイメージングが可能な超解像顕微鏡はこれまで様々な手法が報告されており、いくつかの超解像顕微鏡は既に市販され、特別な技術がなくても使用できるようになった。しかし、in vivoイメージングなど細胞組織深部イメージングにおける超解像顕微鏡応用についてはまだ研究段階である。本稿ではSTED顕微鏡法に焦点を当ててその背景を簡単に概説し、最近の論文をもとに細胞組織深部イメージング応用について紹介する。(著者抄録)

  • STED顕微鏡による細胞組織深部超解像イメージングについて Reviewed

    新岡宏彦

    BIO Clinica   2022.9

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    Super-resolution Imaging of Deep Cellular Tissue Using STED Microscopy

  • 高速非線形ラマン散乱硬性内視鏡による神経イメージング

    大和尚記, 新岡宏彦, 三宅淳, 橋本守

    光学   2022.4

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    Nervesegmentationandaccelerationofnervelmagingwithcoherentramanscattering rigid endoscopy by deep leaming

  • 深層学習を用いた甲状腺細胞診自動診断システム (AI differential diagnosis for cytology of the thyroid:ADDICT)の開発とその現状

    新岡宏彦, 廣川満良, 鈴木彩菜, 安部政俊, 新井悠介, 式見彰浩, 長原 一, 宮内 昭

    Pharm Tech Japan   2022.2

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    Development of AI differential diagnosis for cytology of the thyroid(ADDICT) using deep learning and its current status

  • デジタルトランスフォーメーションで変わる医療 深層学習を用いた甲状腺細胞診自動診断システム(AI differential diagnosis for cytology of the thyroid:ADDICT)の開発とその現状

    新岡 宏彦, 廣川 満良, 鈴木 彩菜, 安部 政俊, 新井 悠介, 式見 彰浩, 長原 一, 宮内 昭

    PHARM TECH JAPAN   38 ( 2 )   247 - 254   2022.2   ISSN:0910-4739

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  • 画像診断におけるArtificial Intelligenceの臨床応用 食道癌リンパ節転移診断能に関する検討

    林 芳矩, 新岡 宏彦, 牧野 知紀, 兼子 晃寛, 小林 照之, 梁川 雅弘, 長原 一, 三宅 淳, 富山 憲幸, 江口 英利, 土岐 祐一郎

    日本臨床外科学会雑誌   2021.10

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  • 心臓病における個別化医療・先制医療 冠動脈光干渉断層イメージングのAI深層学習によるプラーク診断と冠動脈イベント予測

    久米 輝善, 新岡 宏彦, 久保 隆史, 添田 恒有, 渡邊 真言, 山田 亮太郎, 坂田 泰史, 宮本 恵宏, 三宅 淳, 赤阪 隆史, 斎藤 能彦, 上村 史朗

    日本心臓病学会学術集会抄録   2021.9

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  • 内視鏡下外科手術の新しい眼 深層学習による非線形ラマン硬性鏡観察の高速化

    大和尚記, 新岡宏彦, 三宅淳, 橋本守

    光学   2021.8

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  • 深層学習AIを搭載した光イメージング医療機器開発

    新岡 宏彦, 熊本 康昭, 三宅 淳, 松本 辰也, 高松 哲郎

    光アライアンス   2021.5

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  • Terahertz-induced martensitic transformation in partially stabilized zirconia

    Masaya Nagai, Yuhei Higashitani, Masaaki Ashida, Koichi Kusakabe, Hirohiko Niioka, Azusa Hattori, Hidekazu Tanaka, Goro Isoyama, Norimasa Ozaki

    2021.1

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    <title>Abstract</title>
    Martensitic crystal structures are usually obtained by rapid thermal quenching of certain alloys, which induces stress and subsequent shear deformation. Here, we demonstrate that it is also possible to intentionally excite a suitable transverse acoustic phonon mode to induce a local shear deformation. We irradiate the surface of a partially stabilized zirconia plate with intense terahertz pulses and verify martensitic transformation from the tetragonal to the monoclinic phases by Raman spectroscopy and the observed destructive spallation of the zirconia microcrystals. We calculate the phonon modes in tetragonal zirconia and determine the effective channel that triggers the transformation. This mode can be excited via the Klemens process. Since terahertz pulses can induce a specific local shear deformation beyond thermal equilibrium, they can be used to elucidate phase transformation mechanisms with dynamical approaches. Terahertz-induced martensitic transformation is considered to be useful for material strengthening and shape memory ceramics.

    DOI: 10.21203/rs.3.rs-130295/v1

  • 循環器Precision Medicineが開く未来

    坂田泰史, 片岡雅晴, 野村征太郎, 新岡宏彦

    CARDIAC PRACTICE   2020.10

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  • Artificial IntelligenceによるCT画像を用いた食道癌リンパ節転移診断能の検討

    林 芳矩, 新岡 宏彦, 牧野 知紀, 小林 照之, 山崎 翔平, 梁川 雅弘, 山崎 誠, 長原 一, 三宅 淳, 富山 憲幸, 江口 英利, 土岐 祐一郎

    日本臨床外科学会雑誌   2020.10

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  • AIによるバイオメディカル画像解析と光イメージング装置開発

    新岡宏彦, 大和尚記, 三宅淳, 橋本守

    O plus E   2020.7

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  • エルビウム添加ナノ粒子の波長1550 nm帯励起によるアップコンバージョン発光を用いた深部イメージング

    山中 真仁, 新岡 宏彦, 古川 太一, 西澤 典彦

    分光研究   2019.10

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  • Deep learningによるCT画像を用いた食道癌リンパ節転移診断能の検討

    小林 照之, 牧野 知紀, 新岡 宏彦, 山崎 誠, 田中 晃司, 梁川 雅弘, 長原 一, 三宅 淳, 森 正樹, 土岐 祐一郎

    日本消化器外科学会総会   2019.7

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  • Artificial Intelligenceを用いた食道癌右反回神経リンパ節のCT転移診断能の検討

    小林 照之, 新岡 宏彦, 牧野 知紀, 山崎 誠, 田中 晃司, 梁川 雅弘, 長原 一, 三宅 淳, 森 正樹, 土岐 祐一郎

    日本食道学会学術集会プログラム・抄録集   2019.6

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  • Deep-UV excitation fluorescence imaging for rapid and accurate detection of lymph node metastasis in human gastric cancer Reviewed

    Tatsuya Matsumoto, Yasuaki Kumamoto, Hirohiko Niioka, Hideo Tanaka, Jun Miyake, Tetsuro Takamatsu

    Proc. SPIE Photonics WEST BiOS2019   2019.2

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    Deep-UV excitation fluorescence imaging for rapid and accurate detection of lymph node metastasis in human gastric cancer

  • Near-infrared fluorescence imaging by using high nonlinear fluorescence responses of Er3+-doped nanoparticles under the excitation at 1520-1600 nm wavelength region Reviewed

    Masahito Yamanaka, Yoshiki Akino, Hirohiko Niioka, Taichi Furukawa, Norihiko Nishizawa

    Proc. SPIE Photonics WEST BiOS2019   2019.2

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    Near-infrared fluorescence imaging by using high nonlinear fluorescence responses of Er3+-doped nanoparticles under the excitation at 1520-1600 nm wavelength region

  • Near-infrared fluorescence imaging at 1030 nm wavelength region with Yb doped nanoparticles Reviewed

    Yoshiki Akino, Masahito Yamanaka, Hirohiko Niioka, Taichi Furukawa, Norihiko Nishizawa

    Proc. SPIE Photonics WEST BiOS2019   2019.2

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    Near-infrared fluorescence imaging at 1030 nm wavelength region with Yb doped nanoparticles

  • 人工知能・ディープラーニングの医学応用

    三宅淳, 大東寛典, 新岡宏彦, 朴 啓彰

    BRAIN and NERVE   2019.1

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  • ディープラーニングの医療応用に向けた期待

    三宅淳, 田川聖一, 新岡宏彦

    インナービジョン7月号   2018.6

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  • 人工知能 Deep Learning の医学応用

    三宅淳, 田川聖一, 新岡宏彦

    医用画像情報学会誌 Vol. 34, No. 3, 120-125 (2017)   2017.10

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    Medical Application of Deep Learning
    <p>Deep learning has a great potential in biotechnology and medicine. Development of the method gives usextracting meaningful information on drug discovery and medical care. Conceptual understanding of diseases, effectivenessof drugs, evaluation of recovery, telemedicine etc, could be realized from patient's medical records, MRI and CT images,pathological images, DNA sequences. In this review, as a basis for aiming at the development of medical applications, weshould outline the nature and potential of deep learning. Difference form natural science has to be emphasized. Artificialintelligence(deep learning)is a method of categorization, expanding "recognition" which is the essence of diagnosis inmedical application.</p>

    DOI: 10.11318/mii.34.120

  • ディープラーニングのバイオテクノロジーへの応用可能性

    三宅淳, 山本修也, 島林真人, 田川聖一, 新岡宏彦

    日本化学会 バイオテクノロジー部会 NEWS LTTER   2017.8

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  • 人工知能を用いた胃癌の病理画像診断

    新岡 宏彦, 柳本 舎那, 浅谷 学嗣, 田川 聖一, 椙村 春彦, 三宅 淳

    日本病理学会会誌   2017.3

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    人工知能を用いた胃癌の病理画像診断

  • カソードルミネッセンス顕微鏡と近赤外顕微鏡によるマルチモーダルイメージング

    新岡宏彦, 福島昌一郎, 古川太一, 橋本守

    光アライアンス   2017.1

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  • NIR-II近赤外領域における移植幹細胞in vivo蛍光イメージング

    湯川博, 小林香央里, 新岡宏彦, 亀山達也, 佐藤和秀, 鳥本司, 石川哲也, 馬場嘉信

    月刊BIO INDUSTRY   2017.1

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  • ディープラーニングのバイオへの応用

    新岡 宏彦, 山本 修也, 大東 寛典, 浅谷 学嗣, 三宅 淳

    月刊機能材料   2016.10

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  • 1C11 カソードルミネッセンス顕微鏡を用いた液中ナノバイオイメージング

    古川 太一, 福島 昌一郎, 新岡 宏彦, 一宮 正義, 芦田 昌明, 三宅 淳, 橋本 守

    バイオエンジニアリング講演会講演論文集   2016.1

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    1C11 Nanobioimaging in wet-condition using cathodoluminescence microscopy
    We demonstrate nano-bioimaging in wet-condition using cathodoluminescence (CL) of rare-earth doped phosphors. An SEM-CL imaging system is used to observe wet-condition CL, and consists of an SEM, an ellipsoidal mirror, an optical fiber bundle and a detection part based on dichroic mirrors, which can detect 3 color signals simultaneously. Specimens were placed in a capsule having a vacuum sealing thin film to maintain atmospheric pressure inside the capsule. As CL nanoprobes, Y_2O_3:Eu and Y_2O_3:Tb rare-earth doped nanophosphors (red and green emission) were synthesized by homogeneous precipitation method. Two kinds of nanophosphors were introduced into HeLa cells via endocytotic process. After the fixation, the cellular structures were stained by osmium tetroxide for making the contrast of secondary electron. Both cellular structural image (such as lipids) and CL image were simultaneously observed. The spatial resolution of CL microscopy is similar to that of SEM. Correlative imaging of SEM and CL microscopy was succeeded in wet condition. This multimodal/correlative imaging method enables us detail understanding to reveal the cellular functions. We believe that our new nanobioimaging method using CL and rare-earth doped phosphors will be a useful correlative imaging technique.

  • B204 近赤外光・電子顕微鏡による相関バイオイメージング(B2-1 分子・細胞計測)

    福島 昌一郎, 新岡 宏彦, 一宮 正義, 芦田 昌明, 三宅 淳, 荒木 勉, 橋本 守

    バイオフロンティア講演会講演論文集   2014.10

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    B204 Correlative bioimaging with near-infrared and electron microscopy

  • 多焦点リアルタイムCARS顕微鏡による細胞応答観測

    橋本 守, Harsono Cahyadi, 南川 丈夫, 新岡 宏彦, 荒木 勉

    オプトロニクス   2014.5

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    Realtime cellar response observation by multi-focus CARS microscopy

  • 希土類添加ナノ蛍光体粒子を用いたカソードルミネッセンス・蛍光細胞イメージング

    新岡 宏彦, 古川 太一, 橋本 守

    顕微鏡   2014.4

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  • 高速広帯域波長走査レーザを光源とした多焦点CARS顕微鏡

    橋本 守, Harsono Cahyadi, 新岡 宏彦, 荒木 勉

    光アライアンス   2014.3

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  • Tens nanometer scale cathodoluminescence bioimaging with rare-earth doped nanophosphors

    Shoichiro Fukushima, Hirohiko Niioka, Masayoshi Ichimiya, Masayoshi Ichimiya, Jun Miyake, Masaaki Ashida, Tsutomu Araki, Mamoru Hashimoto

    JSAP-OSA Joint Symposia, JSAP 2014   2014.1

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    Tens nanometer scale cathodoluminescence bioimaging with rare-earth doped nanophosphors

  • Multimodal bioimaging probes based on lanthanide doped Gd2O3 nanophosphors

    Doan T. Kim Dung, Shoichiro Fukushima, Hirohiko Niioka, Masayoshi Ichimiya, Masayoshi Ichimiya, Masaaki Ashida, Tsutomu Araki, Mamoru Hashimoto, Jun Miyake

    JSAP-OSA Joint Symposia, JSAP 2014   2014.1

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    Multimodal bioimaging probes based on lanthanide doped Gd2O3 nanophosphors

  • Observation of anhydrated and hydrated DAST crystals using multiplex fourth order Raman microscope

    Chikako Ninagawa, Hirohiko Niioka, Tsutomu Araki, Mamoru Hashimoto

    JSAP-OSA Joint Symposia, JSAP 2014   2014.1

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    Observation of anhydrated and hydrated DAST crystals using multiplex fourth order Raman microscope

  • Towards multicolor correlative light and cathodoluminescence imaging with using upconversion nanophosphors

    S. Fukushima, T. Furukawa, H. Niioka, M. Ichimiya, M. Ichimiya, T. Nagata, J. Miyake, M. Ashida, T. Araki, M. Hashimoto

    Optics InfoBase Conference Papers   2013.12

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    Towards multicolor correlative light and cathodoluminescence imaging with using upconversion nanophosphors

  • 7PM1-A-4 カソードルミネッセンス顕微鏡を用いた細胞のナノ・イメージング(7PM1-A バイオイメージング(センサシンポジウムとの合同セッション))

    古川 太一, 新岡 宏彦, 福島 昌一郎, 一宮 正義, 永田 智啓, 芦田 昌明, 三宅 淳, 荒木 勉, 橋本 守

    マイクロ・ナノ工学シンポジウム   2013.11

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    7PM1-A-4 Cellular nanoimagig by cathodoluminescence microscope
    Cathodoluminescence (CL) is light emission from the materials excited by accelerated electron beam, and CL microscopy has both molecular specificity and nanometer-order spatial resolution. Because of electron beam excitation the spatial resolution reaches about 10 nm. CL microscopy for biological specimens was performed using cathodoluminescence (CL) of Y_2O_3:Eu, Zn nanophosphors, which have high CL intensity due to the incorporation of Zn. Y_2O_3:Eu, Zn nanophosphors in HeLa cells were also imaged with 254 nm. In addition, we propose a new correlative imaging method using upconversion (UC) fluorescence and cathodoluminescence. The results suggest that correlative microscopy using CL, secondary electrons and fluorescence imaging could enable multi-scale investigation of molecular localization from the nanoscale to the microscale.

  • 排出制御電荷変調素子DOMによる蛍光寿命CMOSイメージセンサ

    安富 啓太, 李 卓, 香川 景一郎, 新岡 宏彦, 橋本 守, 川人 祥二

    映像情報メディア学会技術報告   2012.11

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    A Draining-Only Modulation CMOS Image Sensor for Fluorescence Lifetime Imaging
    The paper presents a time-resolved CMOS image sensor with Draining Only Modulation(DOM) pixels for fluorescence lifetime imaging. The proposed DOM pixels, which enables signal charge transfer without any transfer gates, provides high-speed charge modulation and repetitive accumulation at very low light level. The prototype imager demonstrates loss-free charge accumulation and fluorescence lifetime measurements for different fluorescent samples.

  • OS3-1-3 希土類添加ナノ蛍光体を利用したカソードルミネッセンス細胞イメージング(OS3 マイクロ・ナノ生体医工学(1))

    古川 太一, 新岡 宏彦, 一宮 正義, 永田 智啓, 芦田 昌明, 荒木 勉, 橋本 守

    マイクロ・ナノ工学シンポジウム   2012.10

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    OS3-1-3 Cellular imaging with using cathodoluminescence and rare earth doped nanophosphors
    Bio molecular imaging is important to clarify cellular functions. Cathodoluminescence (CL) is light emission from the materials excited by accelerated electron beam, and CL microscopy has the potential to enable color imaging of individual biomolecular distributions with using immunolabeling at high spatial resolution. Because of electron beam excitation the spatial resolution reaches about 10 nm. In this study, we demonstrated CL imaging for cells using rare-earth doped nanophosphors at high spatial resolution.

  • 7D45 ハイパーラマン分光顕微鏡を用いた生体分子の観測(GS10 生体計測(光計測))

    加納 寛人, 新岡 宏彦, 荒木 勉, 橋本 守

    バイオエンジニアリング講演会講演論文集   2012.1

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    7D45 Observation of biological molecules using hyper-Raman microspectroscopy

  • 7D32 CARS顕微鏡による細胞内抗がん剤のイメージング(GS10 生体計測(イメージング))

    池田 晃平, チャフヤディ ハルソン, 新岡 宏彦, 荒木 勉, 橋本 守

    バイオエンジニアリング講演会講演論文集   2012.1

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    7D32 Intracellular imaging of anticancer drug using CARS microscopy

  • 7D44 ラマン散乱顕微鏡と多変量解析を用いた中性脂肪蓄積心筋血管症と虚血性心筋症の識別(GS10 生体計測(光計測))

    松村 直和, 新岡 宏彦, 池田 善彦, 平野 賢一, 荒木 勉, 橋本 守

    バイオエンジニアリング講演会講演論文集   2012.1

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    7D44 Distinction between triglyceride deposit cardiomyovasculopathy and ischemic cardiomyopathy with Raman microscopy and multivariable analysis

  • ラジアル偏光ビームを用いたSHG顕微計測

    新岡 宏彦, 蘆田 幸一郎, 吉木 啓介, 荒木 勉, 橋本 守

    光学   2010.8

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  • リアルタイムCARS顕微鏡の開発と生細胞観測への応用

    橋本 守, 南川 丈夫, 新岡 宏彦, 荒木 勉

    日本レーザー医学会誌 = The Journal of Japan Society for Laser Medicine   2010.1

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    Dedvelopement of Real-Time CARS Microscope and Application to Living Cell Measurement
    Raman microscopy visualizes molecular spices without any staining, because molecular vibrations that all molecules have are sensitive to molecular spices. We developed a real-time CARS (coherent anti-Stokes Raman scattering, which is one of nonlinear Raman scattering) microscopy system. We demonstrate three dimensional lipid distribution in a cell, laser-induced disruption of a lipid rich organelle, and plasma membrane repairing of disrupted plasma membrane.

    DOI: 10.2530/jslsm.30.421

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Professional Memberships

  • 日本臨床細胞学会

  • メディカルAI学会

  • THE JAPAN SOCIETY OF APPLIED PHYSICS

  • JAPANESE SOCIETY FOR MEDICAL AND BIOLOGICAL ENGINEERING

  • THE JAPANESE SOCIETY OF MICROSCOPY

Other

  • 【資格】

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    普通自動車第一種運転免許/
    高圧ガス製造保安責任者 (乙種化学)/
    衛生工学衛生管理者/
    PADIオープンウォーター・ダイバー

Research Projects

  • 第2、3の生体窓と高次非線形光学効果を駆使した深部超解像蛍光イメージング

    Grant number:23K25178  2022.4 - 2025.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (B)

    山中 真仁, 湯川 博, 新岡 宏彦

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    Grant type:Scientific research funding

    生体内に移植された細胞などの生体内挙動や機能は未だ未知のものが多い。本研究では、第2、第3の生体窓と呼ばれる生体透過性の高い近赤外光、高次非線形な蛍光応答、およびAI技術を駆使することで、生体試料の内部を単一細胞レベルで可視化し、細胞の挙動を詳細に解析できる深部・近赤外・高空間分解能蛍光イメージング技術を開発する。本研究で開発した技術を医療技術の発展に資するイメージング技術へ発展させることを目指す

    CiNii Research

  • 生体深部組織の単一細胞レベル解析を実現する高次非線形光音響顕微鏡技術の確立

    Grant number:22K18441  2022 - 2025

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 第2、3の生体窓と高次非線形光学効果を駆使した深部超解像蛍光イメージング

    Grant number:22H03924  2022 - 2024

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 近赤外光と人工知能技術を用いた細胞組織深部超解像顕微鏡の開発と再生医療応用

    2022 - 2024

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • 光干渉断層イメージングのAI解析に基づく冠動脈疾患の包括的ケアシステムの構築

    Grant number:22K08220  2022 - 2024

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • Development of male infertile model mice by genome editing and comprehensive study of fertilization

    Grant number:21H05033  2021.7 - 2026.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (S)

    伊川 正人, 小沢 学, 新岡 宏彦

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    Grant type:Scientific research funding

    ポストゲノムプロジェクト時代の生命科学研究には、ゲノムに秘められた無数の遺伝情報を生理機能と結びつける、個体レベルで遺伝子機能を解析する手法や、遺伝子組換え動物そのものが必要不可欠である。本研究では、CRISPR/Cas9ゲノム編集に、ウイルスベクター、ES細胞キメラ解析、生殖工学などを組み合わせることで、ゲノム編集マウス作製・解析プラットフォームを完成させる。さらにその応用として、精巣特異的に発現する約400遺伝子をノックアウトし、雄性不妊モデルマウスの開発・解析を通して哺乳類の精子・受精のバイオロジーを究める。

    CiNii Research

  • 非線形ラマン散乱顕微内視鏡の開発と無染色その場診断への応用

    Grant number:21H04950  2021 - 2023

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 第2近赤外窓領域を用いた生体深部超解像イメージング技術の開発と再生医療への応用

    Grant number:20H04503  2020 - 2022

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 近赤外第二領域の光と希土類蛍光プローブを用いた生体深部超解像イメージング

    2020

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • 第3生体窓の光で誘起する非線形光学効果を用いた深部高空間分解能光音響イメージング

    Grant number:19K22961  2019 - 2021

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 光干渉断層イメージングのAI解析に基づく急性心筋梗塞発症予測法の開発

    2019 - 2021

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 肺癌の組織診断および悪性度予測の為の人工知能(深層学習)システムの確立

    Grant number:18K07713  2018 - 2020

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • ラマンスペクトル変化の深層学習による細胞の力学応答解析手法の開発

    Grant number:18K04977  2018 - 2020

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 難治性心筋症疾患特異的iPS細胞を用いた集学的創薬 スクリーニングシステムの開発と実践

    2017 - 2021

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 革新的遠隔管理型心臓リハビリテーションシステムの開発

    2017 - 2019

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • NIR-II蛍光イメージングによる移植幹細胞の炎症組織・臓器への生着機構解明

    Grant number:17H02731  2017 - 2019

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • ハイパースペクトル非線形ラマン散乱イメージングによる人工知能病理診断

    Grant number:17H02793  2017 - 2019

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 第2近赤外窓領域を用いた生体深部1細胞イメージング技術の開発と再生医療への応用

    Grant number:17H04738  2017 - 2019

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 深層学習を用いた統合的画像解析による細胞種および状態の識別

    2016 - 2018

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • 深層学習を用いた非侵襲細胞分化判別

    Grant number:16K12526  2016 - 2017

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 癌転移機構解明に向けた近赤外発光・電顕併用白金ナノプローブと生体ナノ計測法の開発

    Grant number:15H05354  2015 - 2017

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 内部構造および力学的性状の異なる血栓はどうして形成されるのか

    Grant number:15K12510  2015 - 2017

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 光・電子相関顕微鏡法のためのプローブ開発と細胞イメージング応用

    2015 - 2016

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • 多層計測と非線形柔軟物モデルの協調による実時間臓器追跡に関する研究

    Grant number:26282147  2014 - 2016

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 高次非線形ラマン散乱顕微鏡による結晶化モニタリング

    Grant number:25286070  2013 - 2015

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • レーザーアブレーションを用いた希土類添加ナノバイオ蛍光プローブ作製

    2013 - 2014

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • 電子線励起プラズモンを用いたバイオイメージング技術の開発

    Grant number:24656050  2012 - 2013

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 直接細胞内分子観察できる極微小探針の創製

    Grant number:23107006  2011 - 2015

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 細胞・組織の診断と評価のための多次元顕微分子イメージングシステムの開発と応用

    Grant number:23240069  2011 - 2013

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • カソードルミネッセンス顕微鏡による細胞中の高空間分解能蛋白質イメージング

    2011 - 2012

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • カソードルミネッセンス顕微鏡による細胞内蛋白質のマルチカラーナノイメージング

    2011 - 2012

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

  • レーザーアブレーションに対する細胞応答のリアルタイムCARSイメージング

    Grant number:22360027  2010 - 2012

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 非線形ラマン顕微鏡の開発と膜タンパク質の選択的イメージング

    Grant number:22760041  2010 - 2011

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

  • 非線形ラマン効果を用いた膜タンパク質の選択的観測

    2009

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Authorship:Principal investigator  Grant type:Scientific research funding

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Social Activities

  • 第6回全国医療AIコンテスト

    大阪大学AI & Machine learning Society/AI Medical Society (AIMS) オンライン開催  2024.3

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

  • 第5回全国医療AIコンテスト

    神戸大学医学部システム医学研究会 (https://kobemed-sysmed.github.io) オンライン開催  2023.3

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    神戸大学医学部システム医学研究会によるレポート
    https://zenn.dev/kobe_sm/articles/6c06362e03648c

  • 第4回全国医療AIコンテスト

    大阪市立大学 医療×IT研究会 (https://twitter.com/ocu_mit)  オンライン開催  2022.3

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    OMU医療×IT研究会代表のレポート
    http://medical-ai-contest.org/report/

  • 第三回全国医療AIコンテスト

    TMDU 医療IT・数学同好会 T/T (tea party), 東京医科歯科大学M&Dデータ科学センター  パシフィコ横浜, オンライン  2021.3

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    TMDU 医療IT・数学同好会 T/T (tea party)代表のレポート
    https://zenn.dev/tpt_ochanomizu/articles/dad722d9410f0a

  • 第二回全国医療AIコンテスト

    大阪大学AI & Machine learning Society/AIメディカル研究会  2020.9

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    AIMS代表によるレポート
    https://seele10.hatenablog.com/entry/2020/10/21/213014

  • AIMSデータサイエンス初心者講座2020 #1

    阪大AI & Machine learning Society (AIMS)  Zoom (オンライン)  2020.8

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

  • 全国医療AIコンテスト

    AIメディカル研究会  2019.9

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    AIMS代表によるレポート
    https://arailly.hatenablog.com/entry/2019/10/01/011240

  • AI Medical High School 2019~春の陣~

    一般社団法人臨床医工情報学コンソーシアム関西  2019.3

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    対象:高校生と高専生
    内容:AIの基礎を学習
    主催:一般社団法人臨床医工情報学コンソーシアム関西
    共催:一般社団法人ナレッジキャピタル
    協力:NVIDIA、阪大AIメディカル研究会

  • DLI (Deep Learning Institute) Certified Instructor

    NVIDIA  2018.9

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    NVIDIA Deep Learning Institute (DLI) では、AI とアクセラレーテッド コンピューティングに関するハンズオン トレーニングを提供することで、実世界の問題の解決に貢献しています。開発者、データ サイエンティスト、研究者向けに設計された DLI のコンテンツは3つの形式(オンラインコース、オンライン選択科目、インストラクターによるワークショップ)でご利用いただけます。

  • AI Medical High School 2018~夏の陣~

    一般社団法人臨床医工情報学コンソーシアム関西  2018.8

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    対象:高校生と高専生
    内容:AIの基礎を学習
    主催:一般社団法人臨床医工情報学コンソーシアム関西
    共催:一般社団法人ナレッジキャピタル
    協力:阪大AIメディカル研究会

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Media Coverage

  • テラヘルツ光を照射しただけで強靭なセラミックスが一瞬で粉々に!

    ResOU  2023.5

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    テラヘルツ光を照射しただけで強靭なセラミックスが一瞬で粉々に!

  • Raman spectroscopy provides non-invasive way to track cell reprogramming

    2021.2

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    Raman spectroscopy provides non-invasive way to track cell reprogramming

  • 細胞のリプログラミングを追う光技術 -リプログラミングバイオマーカーとしてのラマン散乱光-

    2020.12

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    細胞のリプログラミングを追う光技術 -リプログラミングバイオマーカーとしてのラマン散乱光-

  • 術中病理診断 10分で

    毎日新聞  2019.12

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    術中病理診断 10分で

  • 【論文掲載】深紫外励起蛍光画像と人工知能(AI)解析を用いたリンパ節転移検出法の開発

    2019.12

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    【論文掲載】深紫外励起蛍光画像と人工知能(AI)解析を用いたリンパ節転移検出法の開発

  • がんリンパ節転移 迅速診断 AI併用 病理医と同精度

    読売新聞  2019.12

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    がんリンパ節転移 迅速診断 AI併用 病理医と同精度

  • AI駆使へ「学び直し」

    毎日新聞  2018.5

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    AI駆使へ「学び直し」

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Activities contributing to policy formation, academic promotion, etc.

  • 2023.4 - 2024.3   日本光学会年次学術講演会

    国際協力委員

  • 2022.4 - 2025.3   厚生労働省, 保健医療分野 AI 開発加速コンソーシアム

    構成員

  • 2021.4 - 2025.3   日本光学会年次学術講演会

    プログラム委員

  • 2019.4 - 2024.3   日本顕微鏡学会 顕微鏡計測インフォマティクス研究会

    幹事

  • 2018.4 - 2028.3   一般社団法人 臨床医工情報学 コンソーシアム関西

    研究員

  • 2016.4 - 2018.3   日本顕微鏡学会 様々なイメージング技術研究部会

    幹事

  • 2015.4 - 2016.3   日本顕微鏡学会 様々な極微イメージング若手研究部会

    幹事

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