Researcher Database

（Last updated : 2025-04-05 16:01:32）　

NAKAYAMA RYOHEI

Department / Course College of Science and Engineering Department of Electronic and Computer Engineering

Title / Position Professor

Other Affiliations
1.	Graduate School of Science and Engineering

Academic background
1.	2001/04～2005/03	Doctoral Program (2nd Semester) │ Medical Informatics Course │ Graduate School of Medicine │ Mie University │ Completed
2.	1999/04～2001/03	Doctoral Program (1st Semester) │ Department of Computer Science │ Graduate School of Engineering │ University of Miyazaki │ Completed
3.	1995/04～1999/03	Department of Computer Science │ Faculty of Engineering │ University of Miyazaki │ Graduated

Business career
1.	2005/04/01 ～ 2015/03/31	Assistant Professor │ │

Committee and society
1.	2020/04 ～	Radiological Physics and Technology 編集委員

Research activities
1.		IEEE
2.		SPIE
3.		The Institute of Electronics, Information and Communication Engineers (IEICE)
4.		The Japanese Society of Medical Imaging Technology
5.		Medical　Imaging and Information Sciences
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Subject of research
1.	Study on Medical Image Processing and Analysis for Clinical Application

Research summary
Development of medical image processing and analysis technology and their clinical application Contribution to the society of the fruits of research being raised as the principle of research, we are involved in the research to apply science and engineering technology onto medical science, in the field of computer vision and human-computer interaction. Regarding computer vision, research is being conducted on methods to enhance and visualize lesions included in the medical image using image processing technologies, such as filter banks, and ultra-resolution technology, and on enhancement of the quality and resolution of medical images. For human-computer interaction, we are involved in the research of how to analyze the medical image, and how the analysis results should be presented to the physician in order to make it most useful for diagnostic imaging, from the viewpoint of cognitive psychology and interactive theory, using pattern recognition and artificial intelligence. Our activities are being conducted to introduce these fruits of our research into hospital information systems and cloud-type Web systems, and to take part in system design, ranging from identification of problems for their clinical application to finding their solutions, and to apply them in actual medical practice scene.

Present specialized field
Intelligent informatics, Life / Health / Medical informatics, Medical systems, Computational science, Measurement engineering, Radiation science (Keyword：medical image, diagnosis support, image processing, image analysis, intelligent information, pattern recognition, artificial intelligence, filter bank, superresolution processing)

Books
1.	2017/03	Image-Based Computer-Assisted Radiation Therapy │ ,pp.41-66

Papers
1.	2025/04	Unsupervised Video Anomaly Detection using Video Vision Transformer and Adversarial Training │ IEEE Access │ 13,pp.56169-56179
2.	2025/03	Anomaly Detection Scheme for Lung CT Images Using Vector Quantized Variational Auto-Encoder with Support Vector Data Description Radiological Physics and Technology │ Radiological Physics and Technology │ 18 (1),pp.17-26
3.	2025/03	Computerized Classification Method for Significant Coronary Artery Stenosis on Whole-Heart Coronary MRA Using 3D Convolutional Neural Networks with Attention Mechanisms │ Radiological Physics and Technology │ 18 (1),pp.219-226
4.	2025/03	Semantic Segmentation for Individual Thigh Skeletal Muscles of Athletes on Magnetic Resonance Images │ Radiological Physics and Technology │ Online ahead of print.
5.	2024/12	Computerized Classification Method for Molecular Subtypes of Low-grade Gliomas on Brain MR Images Using Modified ArcFace with Gram–Schmidt Orthogonalization │ IEEE Access │ 12,pp.194540-194550
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Academic conference presentation
1.	2025/03	Anomaly Detection for ECG Using LSTM Autoencoder with Attention Mechanisms
2.	2025/03	Anomaly Detection for Lung CT Images Using Masked Autoencoder with Vision Transformer
3.	2025/03	Anomaly Detection for PET Images Using PatchCore with Normalizing Flow and Learnable Positional Encoding
4.	2025/03	Computerized Attenuation Correction of Liver SPECT Images with Extended 3D-pix2pix Model Using Common Latent Variables from Pre- and Post-Attenuation Correction
5.	2025/02	Anomaly Detection for PET Images Using Self-Attention PatchCore with Normalizing Flow
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Winning science prize
1.	2025/03	Research Institute of Signal Processing Student Paper Award NCSP'25 (Anomaly Detection for PET Images Using Self-Attention PatchCore with Normalizing Flow)
2.	2025/03	Research Institute of Signal Processing Student Paper Award NCSP'25 (Computerized Attenuation Correction of Liver SPECT Images Using Extended 3D-pix2pix Model with Bidirectional Learning)
3.	2020/05	第76回日本放射線技術学会総会学術大会 CyPos Gold Award (Region of Interest Setting by Artificial Intelligence for Regional Myocardial Blood Flow Analysis Using Dynamic Contrast-enhanced CT Imaging)
4.	2018/11	Radiological Society of North America 2018 Award for Certificate of Merit (Optimization Method of Hyper-Parameters in Convolutional Neural Network for Medical Image Application)
5.	2018/11	Radiological Society of North America 2018 Award for Certificate of Merit (Pseudocontinuous Arterial Spin Labeling: Clinical Applications and Usefulness in Head and Neck Entities)
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Grants-in-Aid for Scientific Research -KAKENHI-
1.	2023/04 ～ 2026/03	Integrated assessment of volumetry, liver fibrosis and hepatocyte function │ Grant-in-Aid for Scientific Research(C)
2.	2023/04 ～ 2026/03	Development of imaging map of pancreatic cancer reflecting local tissue properties by using image analysis technology │ Grant-in-Aid for Scientific Research(C)
3.	2023/04 ～ 2026/03	Computerized classification method for molecular subtypes of gliomas in brain MRI images using deep learning with a limited number of training data │ Grant-in-Aid for Scientific Research(C)
4.	2020/04 ～ 2023/03	Development of integrated diagnostic method combining the assessment of hepatic intracellular volume and the assessment of hepatic cellular function for predicting liver function after hepatectomy │ Grant-in-Aid for Scientific Research(C)
5.	2020/04 ～ 2023/03	Diagnostic evaluation of early stage lung cancer using deep learning-based analysis of CT images │ Grant-in-Aid for Scientific Research(C)
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External Researcher ID
ORCID ID
0000-0003-0181-7496