| 1. |
Saori Sasaki, Shoko Miyauchi, Ryo Takigawa, Development of a novel method for preparing physically cross-linked Poly(vinyl alcohol) gels, MRM2023, 2023.12. |
| 2. |
Chujie Chang, Shoko Miyauchi, Ken'ichi Morooka, Ryo Kurazume, Oscar Martinez Mozos, FusionNet: a frame interpolation network for 4D heart models, Joint MICCAI Workshop on Time-Series Data Analytics and Learning (MTSAIL) and Lesion Evaluation and Assessment with Follow-Up (LEAF), 2023.10. |
| 3. |
Shinji Tarumi, Mayumi Suzuki, hanae yoshida, Shoko Miyauchi, Ryo Kurazume, Personalized Federated Learning for Institutional Prediction Model using Electronic Health Records: A Covariate Adjustment Approach, 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2023.07. |
| 4. |
Shunsuke Takashima, Shoko Miyauchi, Ken’ichi Morooka, and Ryo Kurazume, Diagnostic support system for coronary artery disease using dynamic heart shapes and metadata, Computer Assisted Radiology and Surgery, 2023.06. |
| 5. |
TowakoTanimura, Chihiro Tanikawa, Shoko Miyauchi, Ken’ichiMorooka, Hajime Nagahara, Takashi Yamashiro, Artificial intelligence system that estimates the GOSLON Yardstick index in patients with unilateral cleft lip and palate, 14th International CLEFT Congress, 2022.07. |
| 6. |
Fumiaki Ichihashi, Akira Koyama, Tetsuya Akashi, Shoko Miyauchi, Ken'ichi Morooka, Hajime Hojo, Hisahiro Einaga, Toshiaki Tanigaki, Hiroyuki Shinada, Yasukazu Murakami, Automatic Hologram Acquisition of Pt Catalyst Nanoparticles on TiO2 Using Particle Detection with Image Processing and AI Classification, Microscopy and Microanalysis, 2021.08. |
| 7. |
Bilel Daoud, Ken’ichi Morooka, Shoko Miyauchi, Ryo Kurazume, Wafa Mnejja, Leila Farhat, Jamel Daoud, A Deep Learning-Based Method for Predicting Volumes of Nasopharyngeal Carcinoma for Adaptive Radiation Therapy Treatment, 25th International Conference on Pattern Recognition (ICPR2020), 2021.01. |
| 8. |
Tokuo Tsuji, Sho Tajima, Yosuke Suzuki, Tetsuyou Watanabe, Shoko Miyauchi, Ken'ichi Morooka, Kensuke Harada, Hiroaki Seki, Motion Generation by Learning Relationship between Object Shapes and Human Motions, International Conference on Artificial Life and Robotics, 2021.01. |
| 9. |
Bilel Daoud, Ken’ichi Morooka, Shoko Miyauchi, Ryo Kurazume, Wafa Mnejja, Farhat Leila, Jamel Daoud, A Method for Predicting Dose Distribution of Nasopharyngeal Carcinoma Cases by Multiple Deep Neural Networks, The 4th International Conference on Imaging, Vision & Pattern Recognition (IVPR), 2020.08. |
| 10. |
A. Umehara, K. Morooka, J. Mutaguchi, S. Kobayashi, S. Miyauchi, R. Kurazume, M. Eto, Bladder cancer segmentation from cystoscopic images by encoder-decoder network, CARS 2020 Computer Assisted Radiology and Surgery, 2020.06. |
| 11. |
Takahiro Yamaguchi, Hajime Nagahara, Ken'ichi Morooka, Yuta Nakashima, Yuki Uranishi, Shoko Miyauchi, and Ryo Kurazume, 3D Image Reconstruction from Multi-focus Microscopic Images, Pacific-Rim Symposium on Image and Video Technology, PSIVT, Deep Medical Imaging Workshop, 2019.11. |
| 12. |
Ken’ich Morooka, Xueru Zhang, Shoko Miyauchi, Ryo Kurazume, and Eiji Ohno, GAN-based Method for Synthesizing Multi-Focus Cell Images, Pacific-Rim Symposium on Image and Video Technology, PSIVT, Deep Medical Imaging Workshop, 2019.11. |
| 13. |
Bilel Daoud, Ken’ichi Morooka, Shoko Miyauchi, Ryo Kurazume, Wafa Mnejja, Leila Farhat, Jamel Daoud, Dose Distribution Prediction for Optimal Treamtment of Modern External Beam Radiation Therapy for Nasopharyngeal Carcinoma, MICCAI 2019 Workshop on Artificial Intelligence in Radiation Therapy, 2019.10. |
| 14. |
Aoi Shinjo, Atsushi Saito, Tetsuya Takakuwa, Shigehito Yamada, Hidekata Hontani, Hiroshi Matsuzoe, Shoko Miyauchi, Ken’ichi Morooka, Akinobu Shimizu, Spatiotemporal Statistical Model of Anatomical Landmarks on a Human Embryonic Brain, Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures: First International Workshop, UNSURE 2019, and 8th International Workshop, CLIP 2019, Held in Conjunction with MICCAI 2019, 2019.10. |
| 15. |
Shoko Miyauchi, Ken'ichi Morooka, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume, Brain volume mapping for constructing volumetric statistical shape model, International Forum on Medical Imaging in Asia 2019, 2019.01, We propose a new method for mapping onto a brain volume model including inner organs with complicated shapes such as lateral ventricles. The proposed method is based on a volumetric Self-organizing Deformable Model (vSDM) which allows to control the mapping positions of inner organs while preserving geometrical features before and after the mapping. The control sometimes causes the self-intersection of the volume model. The solution for the self-intersection in vSDM is to move vertices of the volume model. However, when the inner organ has complicated shape, the vertex movement cannot always correct the self-intersection. To solve this problem, we extend vSDM by introducing a new process of editing the mesh structure of the volume model. Moreover, by applying the proposed method to six brain volume models, a volumetric Statistical Shape Model (SSM) is constructed which represents the shape variations of not only brain surface but also brain inner organs. From experimental results, we confirmed the volumetric SSM has an acceptable performance compared with general surface SSMs generated by organ surface models.. |
| 16. |
Ken'ichi Morooka, Shoko Miyauchi, Xian Chen, Ryo Kurazume, Hexahedron Model Generation of Human Organ by Self-Organizing Deformable Model, 2018 World Automation Congress, WAC 2018, 2018.08, This paper presents a new method for generating object mesh models composed of hexahedra. The proposed method is based on a self-organizing deformable model (SDM) which is a deformable surface model guided by competitive learning and an energy minimization approach. Extending the SDM, the proposed method generates a hexahedral mesh model of a target object by fitting a cuboid composed of rectangular voxels to the object. Moreover, the shape of each hexahedron in the model is corrected by dividing the hexahedron into sub-hexahedra and moving the nodes of the hexahedron. From our experimental results, the proposed method obtains the hexahedral mesh model which consists of many regular hexahedra while recovering the shape of the object.. |
| 17. |
Ken'ichi Morooka, Shoko Miyauchi, Xian Chen, Ryo Kurazume, Hexahedron Model Generation of Human Organ by Self-Organizing Deformable Model, World Automation Congress, 2018.06. |
| 18. |
Shoko Miyauchi, Ken’ichi Morooka, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume, Efficient Geometrical Feature Preserving Mapping for Organ Surface Model, IEEE International Symposium on Biomedical Imaging, 2018.04. |
| 19. |
Shoko Miyauchi, Ken'ichi Morooka, Sho Sasaki, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Kazuhiro Samura, Ryo Kurazume, “Brain Atlas Construction by Non-Rigid Registration of Brain Block Models, CARS 2017 Computer Assisted Radiology and Surgery, 2017.06. |
| 20. |
Shoko Miyauchi, Ken'ichi Morooka, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume, Angle- and Volume-Preserving Mapping of Organ Volume Model Based on modified Self-organizing Deformable Model, 23rd International Conference on Pattern Recognition (ICPR 2016), 2016.12. |
| 21. |
Shoko Miyauchi, Ken’ichi Morooka, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume, A Method for Mapping Tissue Volume Model onto Target Volume Using Volumetric Self-organizing Deformable Model, SPIE Medical Imaging 2016, 2016.03. |
| 22. |
Shoko Miyauchi, Ken’ichi Morooka, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume, Geometrical Features Preserving Parameterization for Vertebra, The 2014 Biomedical Engineering International Conference (BMEiCON-2014), 2014.11. |
| 23. |
Shoko Miyauchi, Ken'ichi Morooka, Yasushi Miyagi, Takaichi Fukuda, Tokuo Tsuji, and Ryo Kurazume, Tissue Surface Model Mapping onto Arbitrary Target Surface Based on Self-organizing Deformable Model, Workshop on Computer Vision at the 4th International Conference on Emerging Security Technologies, 2013.09. |
