著書

• Rahmaniar W, Deng Z., Yang Y., Jin Z., Suzuki K.. Decentralized Diagnostics: The Role of Federated Learning in Modern Medical Imaging, Advances in Intelligent Disease Diagnosis and Treatment, Springer, pp. 223-239, Sept. 2024.

国際会議発表 (査読有り)

• Qu T., Yang Y., Jin Z., Suzuki K.. Annotation-free AI learning of lung nodule segmentation in CT using weakly-supervised Massive -training Artificial neural networks, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA 2024), Dec. 2024.
• Dai P., Ou Y., Yang Y., Liu D., Hashimoto M., Jinzaki M., Miyake M., Suzuki K.. SaSaMIM: Synthetic Anatomical Semantics-Aware Masked Image Modeling for Colon Tumor Segmentation in Non-contrast Abdominal Computed Tomography, The 27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2024), Lecture notes in computer science, LNCS, Vol. 15011, pp. 567–578, Oct. 2024.
• Yuqiao Yang, Ze Jin, Fumihiko Nakatani, Mototaka Miyake, Kenji Suzuki. “Small-data” Patch-wise Multi-dimensional Output Deep-learning for Rare Cancer Diagnosis in MRI under Limited Sample-size Situation, 21st IEEE International Symposium on Biomedical Imaging (ISBI 2024), May 2024.
• Yang Y., Jin Z., Suzuki K.. Federated learning - Game changing AI concept to train AI without sending patient data out from hospitals, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2023.
• Yang Y., Jin Z., Nakatani F., Miyake M., Suzuki K.. Development of a small-data deep-learning model based on an MTANN for soft tissue sarcoma diagnosis in MRI, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2023.
• Ze Jin, Maolin Pang, Yuqiao Yang, Fahad Parvez Mahdi, Tianyi Qu, Ren Sasage, Kenji Suzuki. Explaining Massive-Training Artificial Neural Networks in Medical Image Analysis Task Through Visualizing Functions Within the Models, The 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), Lecture notes in computer science, LNCS, Oct. 2023.
• Yang Y., Jin Z., Nakatani F., Miyake M., Suzuki K.. AI-aided Diagnosis of Rare Soft-Tissue Sarcoma by Means of Massive-Training Artificial Neural Network (MTANN), 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2023), July 2023.
• Zhipeng Deng, Yuqiao Yang, Ze Jin, Kenji Suzuki. FedAL: An Federated Active Learning Framework for Efficient Labeling in Skin Lesion Analysis, International Conference on Systems, Man, and Cybernetics (IEEE SMC 2022), Oct. 2022.
• Yuqiao Yang, Ze Jin, Kenji Suzuki. Federated Tumor Segmentation with Patch-wise Deep Learning Model, 25th International Conference on Medical Image Computing and Computer Assisted InterventionInternational (MICCAI) Workshop on machine learning in medical imaging (MLMI), Sept. 2022.
• Yuqiao Yang, Ze Jin, Kenji Suzuki. Federated Learning Coupled with Massive-Training Artificial Neural Networks in Tumor Segmentation in CT Images., The 44th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2022), July 2022.
• Sato M., Yang Y., Jin Z., Suzuki K.. Segmentation of Liver Tumor in Hepatic CT by Using MTANN Deep Learning with Small Training Dataset Size, The 6th International Symposium on Biomedical Engineering (ISBE2021), Dec. 2021.

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