@book{CTT100925780,
  author = {Rahmaniar W and Deng Z. and Yang Y. and Jin Z. and Suzuki K.},
  title = {Decentralized Diagnostics: The Role of Federated Learning in Modern Medical Imaging},
  publisher = {Springer},
  year = 2024,
}

@book{CTT100901044,
  author = {Ze Jin and Taiguang Yuan and Yukiko Tokuda and Yasuto Naoi and Noriyuki Tomiyama and Kenji Suzuki},
  title = {Radiomics: Approach to Precision Medicine},
  publisher = {Springer},
  year = 2022,
}

@inproceedings{CTT100919886,
  author = {Kodera S. and Mohammad C.S. and Jin Z. and Watadani T. and Abe O. and Suzuki K.},
  title = {Super-efficient AI for lung nodule classification in CT based on small-data massive-training artificial neural network (MTANN)},
  booktitle = {},
  year = 2024,
}

@inproceedings{CTT100919884,
  author = {Deng Z. and Jin Z. and Suzuki K.},
  title = {Dual-domain MTANN for virtual high-dose imaging in digital breast tomosynthesis (DBT)},
  booktitle = {},
  year = 2024,
}

@inproceedings{CTT100919883,
  author = {Yuan T. and Jin Z. and Tokuda Y. and Tomiyama N. and Naoi Y. and Suzuki K.},
  title = {Forecast of genetic assessments for tumor response to chemotherapy only with pretherapeutic breast MRI by means of radiogenomic imaging biomarker scheme},
  booktitle = {},
  year = 2024,
}

@inproceedings{CTT100919887,
  author = {Zhang C. and Jin Z. and Hori M. and Sofue K. and Murakami T. and Suzuki K.},
  title = {AI-aided diagnostic system providing explanations in LI-RADS language in liver cancer diagnosis using MRI},
  booktitle = {},
  year = 2024,
}

@inproceedings{CTT100919885,
  author = {Qu T. and Yang Y. and Jin Z. and Suzuki K.},
  title = {Annotation-free AI learning of lung nodule segmentation in CT using weakly-supervised Massive -training Artificial neural networks},
  booktitle = {},
  year = 2024,
}

@inproceedings{CTT100911599,
  author = {Yuqiao Yang and Ze Jin and Fumihiko Nakatani and Mototaka Miyake and Kenji Suzuki},
  title = {“Small-data” Patch-wise Multi-dimensional Output Deep-learning for Rare Cancer Diagnosis in MRI under Limited Sample-size Situation},
  booktitle = {},
  year = 2024,
}

@inproceedings{CTT100911585,
  author = {染谷健太郎 and 小寺昇冴 and 押部弘子 and 靳泽 and 鈴木賢治},
  title = {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},
  booktitle = {},
  year = 2024,
}

@inproceedings{CTT100911586,
  author = {井原拓哉 and 脇智彦 and 藤田浩二 and Li Chenggeer and Ze Jin and 押部弘子 and 鈴木賢治},
  title = {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},
  booktitle = {},
  year = 2024,
}

@inproceedings{CTT100907908,
  author = {Kodera S. and Rahmaniar W. and Oshibe H. and Jin Z. and Watadani T. and Abe O. and Suzuki K.},
  title = {Super-Efficient Lung Nodule Classification Using Massive-Training Artificial Neural Network (MTANN) Compact Model on LIDC-IDRI Database},
  booktitle = {},
  year = 2024,
}

@inproceedings{CTT100907904,
  author = {Yang Y. and Jin Z. and Suzuki K.},
  title = {Federated learning - Game changing AI concept to train AI without sending patient data out from hospitals},
  booktitle = {},
  year = 2023,
}

@inproceedings{CTT100907907,
  author = {Yang Y. and Jin Z. and Nakatani F. and Miyake M. and Suzuki K.},
  title = {Development of a small-data deep-learning model based on an MTANN for soft tissue sarcoma diagnosis in MRI},
  booktitle = {},
  year = 2023,
}

@inproceedings{CTT100907906,
  author = {Jin Z. and Pang M. and Qu T. and Oshibe H. and Sasage R. and Suzuki K.},
  title = {Feature Map Visualization for Explaining Black-Box Deep Learning Model in Liver Tumor Segmentation},
  booktitle = {},
  year = 2023,
}

@inproceedings{CTT100907905,
  author = {Yang S. and Xiang M. and Qu T. and Jin Z. and Suzuki K.},
  title = {Reconstruction of Fast Acquisition MRI with Under-sampled K-space Data by Using Massive-Training Artificial Neural Networks (MTANNs)},
  booktitle = {},
  year = 2023,
}

@inproceedings{CTT100904973,
  author = {Ze Jin and Maolin Pang and Yuqiao Yang and Fahad Parvez Mahdi and Tianyi Qu and Ren Sasage and Kenji Suzuki},
  title = {Explaining Massive-Training Artificial Neural Networks in Medical Image Analysis Task Through Visualizing Functions Within the Models},
  booktitle = {Lecture notes in computer science, LNCS},
  year = 2023,
}

@inproceedings{CTT100891310,
  author = {Deng Z. and Jin Z. and Suzuki K.},
  title = {Radiation Dose Reduction in Digital Breast Tomosynthesis by MTANN with Multi-scale Kernels},
  booktitle = {},
  year = 2023,
}

@inproceedings{CTT100891311,
  author = {Yang Y. and Jin Z. and Nakatani F. and Miyake M. and Suzuki K.},
  title = {AI-aided Diagnosis of Rare Soft-Tissue Sarcoma by Means of Massive-Training Artificial Neural Network (MTANN)},
  booktitle = {},
  year = 2023,
}

@inproceedings{CTT100891312,
  author = {Yang S. and Xiang M. and Qu T. and Jin Z. and Suzuki K.},
  title = {Under-sampled Image Reconstruction in Fast Acquisition MRI with Massive-Training Artificial Neural Networks (MTANNs) Deep Learning Approach},
  booktitle = {},
  year = 2023,
}

@inproceedings{CTT100898547,
  author = {Pang M. and Jin Z. and Qu T. and Mahdi F. P. and Sasage R. and Suzuki K.},
  title = {Functional Model Visualization for Explaining Massive-Training Artificial Neural Network for Liver Tumor Segmentation},
  booktitle = {},
  year = 2023,
}

@inproceedings{CTT100891309,
  author = {Xu L. and Mahdi F. P. and Jin Z. and Noguchi Y. and Murata M. and Suzuki K.},
  title = {Generating simulated fluorescence images for enhancing proteins from optical microscopy images of cells using massive-training artificial neural networks},
  booktitle = {Proceedings of SPIE},
  year = 2023,
}

@inproceedings{CTT100887257,
  author = {Zhipeng Deng and Ze Jin and Kenji Suzuki},
  title = {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},
  booktitle = {},
  year = 2023,
}

@inproceedings{CTT100881599,
  author = {Zhipeng Deng and Yuqiao Yang and Ze Jin and Kenji Suzuki},
  title = {FedAL: An Federated Active Learning Framework for Efficient Labeling in Skin Lesion Analysis},
  booktitle = {},
  year = 2022,
}

@inproceedings{CTT100881601,
  author = {Yuqiao Yang and Ze Jin and Kenji Suzuki},
  title = {Federated Tumor Segmentation with Patch-wise Deep Learning Model},
  booktitle = {},
  year = 2022,
}

@inproceedings{CTT100879354,
  author = {Yuqiao Yang and Ze Jin and Kenji Suzuki},
  title = {Federated Learning Coupled with Massive-Training Artificial Neural Networks in Tumor Segmentation in CT Images.},
  booktitle = {},
  year = 2022,
}

@inproceedings{CTT100862831,
  author = {Onai Y. and Mahdi F. P. and Jin Z. and Suzuki K.},
  title = {Virtual High-Radiation-Dose Image Generation from Low-Radiation-Dose Image in Digital Breast Tomosynthesis (DBT) Using Massive-Training Artificial Neural Network (MTANN)},
  booktitle = {},
  year = 2021,
}

@inproceedings{CTT100862832,
  author = {Sato M. and Yang Y. and Jin Z. and Suzuki K.},
  title = {Segmentation of Liver Tumor in Hepatic CT by Using MTANN Deep Learning with Small Training Dataset Size},
  booktitle = {},
  year = 2021,
}

@inproceedings{CTT100862830,
  author = {Xiang M. and Jin Z. and Suzuki K.},
  title = {Massive-Training Artificial Neural Network (MTANN) for Image Quality Improving in Fast-Acquisition MRI of the Knee},
  booktitle = {},
  year = 2021,
}

@inproceedings{CTT100862828,
  author = {Sato M. and Jin Z. and Suzuki K.},
  title = {Semantic Segmentation of Liver Tumor in Contrast-enhanced Hepatic CT by Using Deep Learning with Hessian-based Enhancer with Small Training Dataset Size},
  booktitle = {},
  year = 2021,
}

@inproceedings{CTT100862829,
  author = {Xiang M. and Jin Z. and Suzuki K.},
  title = {Massive-Training Artificial Neural Network (MTANN) with Special Kernel for Artifact Reduction In Fast-Acquisition MRI of the Knee},
  booktitle = {},
  year = 2021,
}

@inproceedings{CTT100845008,
  author = {Onai Y. and Jin Z. and Suzuki K.},
  title = {Generation of Virtual High-Radiation-Dose Images from Low-Dose Images in Digital Breast Tomosynthesis (DBT) with Massive-Training Artificial Neural Network (MTANN)},
  booktitle = {},
  year = 2021,
}

@inproceedings{CTT100845007,
  author = {Sato M. and Jin Z. and Suzuki K.},
  title = {Small-Training-Set Deep Learning for Semantic Segmentation of Liver Tumors in Contrast-enhanced Hepatic CT},
  booktitle = {},
  year = 2021,
}

@inproceedings{CTT100845006,
  author = {Xiang M. and Jin Z. and Suzuki K.},
  title = {Fast Acquisition MRI of the Knee by Means of Massive-Training Artificial Neural Network (MTANN) with Special Kernel},
  booktitle = {},
  year = 2021,
}

@inproceedings{CTT100828643,
  author = {Taiguang Yuan and Ze Jin and Yukiko Tokuda and Yasuto Naoi and Noriyuki Tomiyama and Takashi Obi and Kenji Suzuki},
  title = {Prediction of Genetically-Evaluated Tumour Responses to Chemotherapy from Breast MRI using Machine Learning with Model Selection},
  booktitle = {Journal of Physics: Conference Series},
  year = 2020,
}

@inproceedings{CTT100828642,
  author = {Taiguang Yuan and Ze Jin and Tokuda Y. and Naoi Y. and Tomiyama N. and Kenji Suzuki},
  title = {MR Imaging biomarkers for Prediction of Genetic Assessment for Breast Cancer Recurrence: A Radiogenomics Study},
  booktitle = {IEICE Technical Report},
  year = 2020,
}

@inproceedings{CTT100828644,
  author = {Taiguang Yuan and Ze Jin and Tokuda Y. and Naoi Y. and Tomiyama N. and Kenji Suzuki},
  title = {Discovery of MR Imaging Biomarkers for Prediction of Pathological Complete Responses to Chemotherapy for Breast Cancer},
  booktitle = {Proceeding of 4th International Symposium on Biomedical Engineering (ISBE2019)},
  year = 2019,
}

@inproceedings{CTT100828645,
  author = {Yuchen Wang and Ze Jin and Tokuda Y. and Naoi Y. and Tomiyama N. and Kenji Suzuki},
  title = {Neural Network Convolution Deep Learning for Semantic Segmentation of Breast Tumor in MRI},
  booktitle = {Proceeding of 4th International Symposium on Biomedical Engineering (ISBE2019)},
  year = 2019,
}

@inproceedings{CTT100828647,
  author = {Taiguang Yuan and Ze Jin and Tokuda, Y. and Naoi, Y. and Tomiyama, N. and Kenji Suzuki},
  title = {Development of deep-learning segmentation for breast cancer in mr images based on neural network convolution},
  booktitle = {Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition},
  year = 2019,
}

@misc{CTT100844665,
  author = {Onai Y. and Jin Z. and Obi T. and Suzuki K.},
  title = {Neural Network Convolution (NNC) Deep Learning for Radiation Dose Reduction in Digital Breast Tomosynthesis (DBT)},
  year = 2020,
}

@misc{CTT100884605,
  author = {鈴木賢治 and JINZE},
  title = {画像処理装置、画像処理方法及びプログラムが格納された非一時的なコンピュータ可読媒体},
  howpublished = {公開特許},
  year = 2022,
  month  = {},
  note   = {PCT/JP2022/008813(2022/03/02), WO 2022/186263(2022/09/09)}
}