Journal Paper

• Yang Y., Sato M., Jin Z., Suzuki K. Patch-based Deep-learning Model with Limited Training Dataset for Liver Tumor Segmentation in Contrast-enhanced Hepatic Computed Tomography, IEEE Access, IEEE, Vol. 13, pp. 86863-86873, May 2025.
• Deng Z., Yang Y., Suzuki K.. Federated Active Learning Framework for Efficient Annotation Strategy in Skin-Lesion Classification, Journal of Investigative Dermatology, vol. 145, no. 2, pp. 303-311, Feb. 2025.
• Rahmaniar W., Deng Z., Yang Y., Jin Z., Suzuki K.. Future of the Medical World: Collaborative Medical Imaging AI with Federated Learning, IEEE Consumer Electronics Magazine, Feb. 2025.

International Conference (Reviewed)

• Zhang H., Yang Y., Jin Z., Suzuki K. Sequence-aware MTANN for Semantic Segmentation of Rare Cancer in Multisequence MRI with Small Data Training, 40th Computer Assisted Radiology and Surgery (CARS 2025), June 2025.
• Kenji Suzuki. BLS-GAN: A Deep Layer Separation Framework for Eliminating Bone Overlap in Conventional Radiographs, The 39th Annual AAAI Conference on Artificial Intelligence (AAAI-25), Mar. 2025.

Patent

• Kenji Suzuki. ネットワーク解析システム、ネットワーク解析方法及びプログラム. Patent. Published. 国立大学法人東京工業大学. 2024/03/08. PCT/JP2024/009074. 2025/01/30. WO 2025/022705. 2025.

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