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.
• 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.
• 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.

International Conference (Reviewed)

• Zhang H., Rahmaniar W., Yang Y., Nakatani F., Miyake M., Suzuki K.. Sequence-Aware MTANN for Segmentation of Rare Soft-Tissue Sarcomas in Multi-Sequence MRI with Missing Sequences, Nov. 2025.
• Yanhong he., Ou Y., Dai P., Yang Y., Jin Z., Suzuki K.:. Orientation-Consistent Patch Sampling Method Based on Centerline for Colon Segmentation in CT, Nov. 2025.
• Dai P., Ou Y., Yang Y., Jin Z., Suzuki K.. GoCa: Trustworthy Multi-Modal RAG with Explicit Thinking Distillation for Reliable Decision-Making in Med-LVLMs, The 28th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2025), Sept. 2025.
• 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.

Domestic Conference (Reviewed)

• Tenma Morikawa, Yafei Ou, Yuqiao Yang, Ze Jin, Kenji Suzuki. Improving Federated Learning for Skin Lesion Classification with Weight Perturbation Optimization to the ETF Classifier, 第44回日本医用画像工学会大会 (JAMIT 2025), Aug. 2025.

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