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鈴木賢治 2023年 研究業績一覧 (24件 / 382件)
論文
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Pavarut S.,
Preedanan W.,
Kumazawa I.,
Suzuki K.,
Kobayashi M.,
Tanaka H.,
Ishioka J.,
Matsuoka Y.,
Fujii Y..
Improving Kidney Tumor Classification With Multi-Modal Medical Images Recovered Partially by Conditional CycleGAN,
IEEE Access,
Vol. 11,
pp. 146250-146261,
Dec. 2023.
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Wahyu Rahmaniar,
Kenji Suzuki,
Ting-Lan Lin.
Auto-CA: Automated Cobb Angle Measurement Based on Vertebrae Detection for Assessment of Spinal Curvature Deformity,
IEEE Transactions on Biomedical Engineering,
pp. 1-10,
Sept. 2023.
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Tomoyuki Shishido,
Yasuhiro Ono,
Itsuo Kumazawa,
Ichiro Iwai,
kenji suzuki.
Artificial intelligence model substantially improves stratum corneum moisture content prediction from visible-light skin images and skin feature factors,
Skin Research and Technology,
Vol. 29,
Issue 8,
July 2023.
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Wongsakorn Preedanan,
Kenji Suzuki,
Toshiaki Kondo,
Masaki Kobayashi,
Hajime Tanaka,
Junichiro Ishioka,
Yoh Matsuoka,
Yasuhisa Fujii,
Itsuo Kumazawa.
Urinary Stones Segmentation in Abdominal X-Ray Images Using Cascaded U-Net Pipeline with Stone-Embedding Augmentation and Lesion-Size Reweighting Approach,
IEEE Access,
vol. 11,
pp. 25702-25712,
Mar. 2023.
公式リンク
国際会議発表 (査読有り)
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Yang S.,
Xiang M.,
Qu T.,
Jin Z.,
Suzuki K..
Reconstruction of Fast Acquisition MRI with Under-sampled K-space Data by Using Massive-Training Artificial Neural Networks (MTANNs),
Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA),
Nov. 2023.
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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.
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Jin Z.,
Pang M.,
Qu T.,
Oshibe H.,
Sasage R.,
Suzuki K..
Feature Map Visualization for Explaining Black-Box Deep Learning Model in Liver Tumor Segmentation,
Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA),
Nov. 2023.
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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.
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Kenji Suzuki.
ROC-Score-Based Ensemble Training for Multiple Deep Learning Modules in Classification between Polyps and Non-Polyps in CT Colonography,
2023 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC),
Oct. 2023.
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Sirisanwannakul K.,
Siripool N.,
Suzuki K.,
Kongprawechnon W.,
Karnjana J..
Detection and Correction of Defective Relative Humidity Data Collected from the Greenhouse Environment Using Nested Kalman Filters with Standard Deviation Analysis,
2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2023),
Oct. 2023.
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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.
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Deng Z.,
Jin Z.,
Suzuki K..
Radiation Dose Reduction in Digital Breast Tomosynthesis by MTANN with Multi-scale Kernels,
45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2023),
July 2023.
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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.
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Yang S.,
Xiang M.,
Qu T.,
Jin Z.,
Suzuki K..
Under-sampled Image Reconstruction in Fast Acquisition MRI with Massive-Training Artificial Neural Networks (MTANNs) Deep Learning Approach,
45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2023),
July 2023.
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Pang M.,
Jin Z.,
Qu T.,
Mahdi F. P.,
Sasage R.,
Suzuki K..
Functional Model Visualization for Explaining Massive-Training Artificial Neural Network for Liver Tumor Segmentation,
45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2023),
July 2023.
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Xu L.,
Mahdi F. P.,
Jin Z.,
Noguchi Y.,
Murata M.,
Suzuki K..
Generating simulated fluorescence images for enhancing proteins from optical microscopy images of cells using massive-training artificial neural networks,
SPIE Medical Imaging (SPIE MI),
Proceedings of SPIE,
Apr. 2023.
公式リンク
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Kenji Suzuki.
AI-aided Diagnosis and Virtual AI Imaging with Small-Data Deep Learning,
The Fifteenth International Conference on eHealth, Telemedicine, and Social Medicine (eTELEMED 2023),
Apr. 2023.
公式リンク
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Zhipeng Deng,
Ze Jin,
Kenji Suzuki.
Radiation Dose Reduction in Digital Breast Tomosynthesis (DBT) by Means of Multi-scale-Kernel Massive-Training Artificial Neural Network (MTANN) for Generating Virtual High-Dose Images,
European Congress of Radiology (ECR 2023),
Mar. 2023.
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Kenji Suzuki.
Deep Residual Massive-Training Artificial Neural Network for Image Denoising,
2023 5th International Conference on Image, Video and Signal Processing (IVSP 2023),
Mar. 2023.
国際会議発表 (査読なし・不明)
その他の論文・著書など
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Wan Azani Mustafa,
Kenji Suzuki.
Special Issue: Editorial Board Members’ Collection Series in “Computer-Aided Diagnosis and Prognosis of Diseases",
Diagnostics,
MDPI,
Mar. 2023.
公式リンク
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Giacinto Barresi,
Sabrina Cipolletta,
Andreas Triantafyllidis,
Kenji Suzuki.
Special issue: Intelligent Systems for One Digital Health,
International Journal of Environmental Research and Public Health,
MDPI,
Feb. 2023.
公式リンク
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Kenji Suzuki,
José Machado.
Special Issue: Feature Papers for AI,
AI,
MDPI,
2023.
公式リンク
特許など
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鈴木賢治.
推定装置、推定方法及びプログラム.
特許.
公開.
国立大学法人東京工業大学.
2022/11/30.
PCT/JP2022/044260.
2023/06/08.
WO 2023-100953.
2023.
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