論文

• Cunyuan Ji, Kengo Oshima, Takumi Urata, Fumikazu Kimura, Keiko Ishii, Takeshi Uehara, Kenji Suzuki, Saori Takeyama, Masahiro Yamaguchi. Transformation from Hematoxylin-and-eosin Staining to Ki-67 Immunohistochemistry Digital Staining Images Using Deep Learning: Experimental Validation on the Labeling Index, Journal of Medical Imaging, Vol. 11, Issue 4, 047501, July 2024.  公式リンク  
  
• Samala R. K., Drukker K., Shukla-Dave A., Chan H. P., Sahiner B., Petrick N., Greenspan H., Mahmood U., Summers R. M., Tourassi G., Deserno T. M., Regge D., Nappi J. J., Yoshida H., Huo Z., Chen Q., Vergara D., Cha K. H., Mazurchuk R., Grizzard K. T., Huisman H., Morra L., Suzuki K., Armato III S. G., Hadjiiski L.. AI and machine learning in medical imaging: key points from development to translation, BJR Artificial Intelligence, Vol. 1, No. 1, Apr. 2024.
• Mahmood U., Shukla-Dave A., Chan H. P., Drukker K., Samala R. K., Chen Q., Vergara D., Greenspan H., Petrick N., Sahiner B., Huo Z., Summers R. M., Cha K. H., Tourassi G., Deserno T. M., Grizzard K. T., Nappi J. J., Yoshida H., Regge D., Mazurchuk R., Suzuki K., Morra L., Huisman H., Armato, III S. G., Hadjiiski L.. Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing, BJR Artificial Intelligence, Vol. 1, No. 1, Mar. 2024.

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)

• Yuan T., Jin Z., Tokuda Y., Tomiyama N., Naoi Y., Suzuki K.. Forecast of genetic assessments for tumor response to chemotherapy only with pretherapeutic breast MRI by means of radiogenomic imaging biomarker scheme, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA 2024), Dec. 2024.
• Zhang C., Jin Z., Hori M., Sofue K., Murakami T., Suzuki K.. AI-aided diagnostic system providing explanations in LI-RADS language in liver cancer diagnosis using MRI, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA 2024), Dec. 2024.
• Kodera S., Mohammad C.S., Jin Z., Watadani T., Abe O., Suzuki K.. Super-efficient AI for lung nodule classification in CT based on small-data massive-training artificial neural network (MTANN), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA 2024), Dec. 2024.
• 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.
• Deng Z., Jin Z., Suzuki K.. Dual-domain MTANN for virtual high-dose imaging in digital breast tomosynthesis (DBT), 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.
• Kodera S., Rahmaniar W., Oshibe H., Jin Z., Watadani T., Abe O., Suzuki K.. Super-Efficient Lung Nodule Classification Using Massive-Training Artificial Neural Network (MTANN) Compact Model on LIDC-IDRI Database, 2024 6th International Conference on Image, Video and Signal Processing (IVSP 2024), Mar. 2024.

国内会議発表 (査読有り)

• 染谷健太郎, 小寺昇冴, 押部弘子, 靳泽, 鈴木賢治. CTにおける複数のMTANNを組み合わせた肺結節のセグメンテーション, メディカルイメージング連合フォーラム2024, Mar. 2024.

国内会議発表 (査読なし・不明)

• Cunyuan Ji, Kengo Oshima, Takumi Urata, Fumikazu Kimura, Keiko Ishii, Takeshi Uehara, Kenji Suzuki, Saori Takeyama, Masahiro Yamaguchi. Predicting the Ki-67 labeling index of endometrioid cancer from the hematoxylin-and-eosin-stained whole slide image, 第22回日本デジタルパソロジー・AI研究会 定時総会, E2, Aug. 2024.  公式リンク  
  
• 井原拓哉, 脇智彦, 藤田浩二, Li Chenggeer, Ze Jin, 押部弘子, 鈴木賢治. スモールデータ深層学習を用いた単純X 線画像での舟状骨骨折検知AI システムの開発, 2023年度生体医歯工学共同研究拠点成果報告会, Mar. 2024.

特許など

• 鈴木賢治. 情報処理システム及び情報処理方法. 特許. 公開. 国立大学法人東京工業大学. 2022/07/08. 特願2022-110448. 2024/01/19. 特開2024-008511. 2024.
• 鈴木賢治, 小尾高史, 鈴木裕之, 石川　雅浩, 小林　直樹. 染色画像推定器学習装置、画像処理装置、染色画像推定器学習方法、画像処理方法、染色画像推定器学習プログラム、及び、画像処理プログラム. 特許. 登録. 国立大学法人東京工業大学, 学校法人埼玉医科大学. 2019/03/06. 特願2019-041046. 2020/09/10. 特開2020-144012. 特許第7470339号. 2024/04/10 2024.

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