記述言語：その他   掲載種別：研究論文（学術雑誌）  

This paper was one of the most downloaded* during its first 12 months
of publication in:
CANCER CYTOPATHOLOGY
Application of deep learning as an ancillary diagnostic tool for thyroid FNA cytology
*Among work published in an issue between 1 January 2022 – 31 December 2022.

DOI： 10.1002/cncy.22669

記述言語：その他   掲載種別：研究論文（学術雑誌）  

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

記述言語：日本語   掲載種別：研究論文（学術雑誌）  

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

DOI： 10.5795/jjscc.61.200

記述言語：日本語   出版者・発行元：(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)

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）  

DOI： 10.1117/12.2609483

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

<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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：その他   掲載種別：研究論文（学術雑誌）  

DOI： 10.1117/1.JBO.24.7.070501

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

記述言語：英語   掲載種別：研究論文（学術雑誌）  

DOI： 10.5757/jkvs.2010.19.6.423

記述言語：英語   掲載種別：研究論文（学術雑誌）  

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

開催年月日： 2022年6月

記述言語：日本語  

国名：その他  

開催年月日： 2022年3月

記述言語：その他  

国名：その他  

開催年月日： 2022年1月

記述言語：日本語  

国名：その他  

開催年月日： 2021年10月

記述言語：日本語  

国名：その他  

開催年月日： 2021年9月

記述言語：日本語  

国名：その他  

開催年月日： 2021年6月

記述言語：日本語  

国名：その他  

開催年月日： 2021年6月

記述言語：日本語  

開催地：幕張メッセ国際会議場   国名：日本国  

開催年月日： 2021年5月

記述言語：日本語  

国名：その他  

開催年月日： 2021年3月

記述言語：英語  

国名：その他  

Prediction of Coronary Plaque Vulnerability Using OCT Images and Deep Learning

開催年月日： 2020年12月

記述言語：日本語  

国名：その他  

開催年月日： 2020年10月

記述言語：日本語  

国名：その他  

開催年月日： 2020年7月

記述言語：英語  

国名：その他  

開催年月日： 2019年12月

記述言語：日本語  

開催地：パシフィコ横浜   国名：日本国  

開催年月日： 2019年11月

記述言語：英語  

開催地：Ichokaikan, Osaka University, Japan   国名：日本国  

開催年月日： 2019年9月

記述言語：日本語  

開催地：岡山大学島津キャンパス   国名：日本国  

開催年月日： 2019年9月

記述言語：英語  

開催地：University of California, San Diego, USA (Online)   国名：アメリカ合衆国  

Bio-Medical Optical Imaging Using Deep Learning

開催年月日： 2019年7月

記述言語：英語  

開催地：Odaiba Miraikan, Tokyo, Japan   国名：日本国  

Bio-Medical imaging supported by deep learning

開催年月日： 2019年7月

記述言語：日本語  

国名：その他  

開催年月日： 2019年6月

記述言語：日本語  

開催地：沖縄コンベンションセンター   国名：日本国  

開催年月日： 2019年6月

記述言語：日本語  

国名：その他  

開催年月日： 2018年11月

記述言語：日本語  

開催地：北海道大学 フロンティア応用化学研究棟   国名：日本国  

開催年月日： 2018年11月

記述言語：日本語  

開催地：北海道大学 フロンティア応用化学研究棟   国名：日本国  

開催年月日： 2018年11月

記述言語：その他  

開催地：名古屋大学工学研究科   国名：日本国  

開催年月日： 2018年11月

記述言語：日本語  

開催地：富山国際会議場   国名：日本国  

開催年月日： 2018年10月

記述言語：日本語  

開催地：統計数理研究所   国名：日本国  

開催年月日： 2018年9月

記述言語：日本語  

開催地：大阪国際会議場 リーガロイヤルホテル大阪   国名：日本国  

開催年月日： 2018年6月

記述言語：日本語  

開催地：札幌コンベンションセンター   国名：日本国  

開催年月日： 2014年8月

記述言語：日本語  

国名：その他  

開催年月日： 2013年12月

記述言語：英語  

開催地：Las Vegas, USA   国名：アメリカ合衆国  

Rare-earth doped Y2O3 nanophosphors for biological cathodoluminescence imaging

開催年月日： 2013年9月

記述言語：日本語  

開催地：同志社大学京田辺キャンパス   国名：日本国  

開催年月日： 2012年10月

記述言語：日本語  

開催地：生理学研究所   国名：日本国  

開催年月日： 2012年5月

記述言語：日本語  

開催地：つくば国際会議場   国名：日本国  

記述言語：日本語  

開催地：パシフィコ横浜   国名：日本国  

記述言語：日本語  

国名：その他  

記述言語：日本語  

国名：日本国  

記述言語：日本語  

開催地：オンライン   国名：日本国  

記述言語：日本語  

開催地：立命館大学東京キャンパス   国名：日本国  

記述言語：日本語  

開催地：オンライン   国名：日本国  

記述言語：日本語  

開催地：徳島大学 ポストLEDフォトニクス研究所   国名：日本国  

記述言語：日本語  

開催地：大阪大学基礎工学研究科・基礎工学国際棟   国名：日本国  

記述言語：日本語  

開催地：リーガロイヤルホテル大阪 タワーウイング2階「桐」   国名：日本国  

記述言語：日本語  

開催地：グランフロント大阪 タワーC カンファレンスルームC04   国名：日本国  

記述言語：日本語  

開催地：大阪産業創造館   国名：日本国  

記述言語：日本語  

開催地：大阪国際会議場   国名：日本国  

記述言語：日本語  

開催地：大阪・梅田 富国生命ビル４F まちラボ A   国名：日本国  

記述言語：英語  

開催地：Icho Kaikan 3F Hall, Osaka University, Osaka, Japan   国名：日本国  

Technologies of Deep Learning for Medical Applications

記述言語：日本語  

開催地：大阪大学中之島センター   国名：日本国  

記述言語：日本語  

開催地：大阪大学最先端医療イノベーションセンター   国名：日本国  

記述言語：日本語  

開催地：奈良先端科学技術大学院大学   国名：日本国  

記述言語：日本語  

開催地：タワーホール船堀   国名：日本国  

記述言語：日本語  

開催地：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   国名：日本国  

記述言語：日本語  

開催地：統計数理研究所   国名：日本国  

記述言語：日本語  

開催地：大阪大学医学部講義棟1階A講堂   国名：日本国  

記述言語：日本語  

開催地：大阪大学 基礎工学研究科   国名：日本国  

記述言語：日本語  

開催地：大阪大学基礎工学研究科・基礎工学国際棟   国名：日本国  

記述言語：日本語  

開催地：Qbic 生命システム研究センター 理化学研究所   国名：日本国  

記述言語：英語  

開催地：Nagoya University, Aichi, Japan   国名：日本国  

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

記述言語：日本語  

開催地：帝京大学医学部   国名：日本国  

記述言語：日本語  

開催地：帝京大学医学部   国名：日本国  

記述言語：日本語  

開催地：大阪大学フォトニクスセンター   国名：日本国  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：英語  

記述言語：英語  

記述言語：英語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：その他  

<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

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：英語  

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

記述言語：英語  

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

記述言語：英語  

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

記述言語：その他  

記述言語：その他  

記述言語：日本語  

<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

記述言語：日本語  

記述言語：日本語  

人工知能を用いた胃癌の病理画像診断

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

記述言語：日本語  

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.

記述言語：日本語  

B204 Correlative bioimaging with near-infrared and electron microscopy

記述言語：日本語  

Realtime cellar response observation by multi-focus CARS microscopy

記述言語：日本語  

記述言語：日本語  

記述言語：その他  

Tens nanometer scale cathodoluminescence bioimaging with rare-earth doped nanophosphors

記述言語：その他  

Multimodal bioimaging probes based on lanthanide doped Gd2O3 nanophosphors

記述言語：その他  

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

記述言語：その他  

Towards multicolor correlative light and cathodoluminescence imaging with using upconversion nanophosphors

記述言語：日本語  

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.

記述言語：日本語  

排出のみの制御によって電荷変調を行うことが可能な排出制御型電荷変調素子DOMとこれを用いた蛍光寿命イメージセンサについて述べる.信号経路から転送ゲートをなくすことで,バリアレスで界面トラップの影響の受けない構造となり,極微弱光に対してもロスのない繰り返し蓄積が可能である.標準CMOSイメージセンサプロセスで時間分解型イメージセンサを試作して得られた評価結果と,これを用いて構築した蛍光寿命顕微鏡システムによる実細胞の観察実験について報告する.

記述言語：日本語  

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.

記述言語：日本語  

7D45 Observation of biological molecules using hyper-Raman microspectroscopy

記述言語：英語  

7D32 Intracellular imaging of anticancer drug using CARS microscopy

記述言語：日本語  

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

記述言語：日本語  

記述言語：日本語  

ラマン分光顕微鏡は，全ての分子が持つ分子振動を観測することで，無染色で分子種を見分けながら可視化する手法である．我々は，非線形なラマン散乱分光であるCARS（Coherent anti-Stokes Raman scattering）分光により，リアルタイムで観測可能なを多焦点CARS 顕微鏡を開発した．本稿では，開発した装置や，これを用いて観測した細胞の3次元イメージ，レーザーアブレーションと組み合わせて，細胞内小器官の破壊や細胞膜の破壊と修復過程の観測に応用した例を紹介する．

DOI： 10.2530/jslsm.30.421

対象：社会人・一般,　学術団体,　企業,　市民団体,　行政機関

対象：社会人・一般,　学術団体,　企業,　市民団体,　行政機関

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

対象：社会人・一般,　学術団体,　企業,　市民団体,　行政機関

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

対象：社会人・一般,　学術団体,　企業,　市民団体,　行政機関

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。

対象：社会人・一般,　学術団体,　企業,　市民団体,　行政機関

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

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」