Book

• 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.

International Conference (Reviewed)

• 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.

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