Researcher Database

（Last updated : 2023-03-10 14:08:19）

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 (Co-authored)

Papers
1.	2022/08	Pseudocontinuous Arterial Spin Labeling: Clinical Applications and Usefulness in Head and Neck Entities │ Cancers │ 14 (16),pp.1-17 (Co-authored)
2.	2022/06	Computerized Classification Method for 1p/19q Codeletion in Low Grade Gliomas from Brain MRI Images Using Three Dimensional Radiomics Features │ Journal of the Institute of Image Electronics Engineers of Japan (IIEEJ) │ in accepted (Co-authored)
3.	2022/05	Tooth Detection for Each Tooth Type by Application of Faster R-CNNs to Divided Analysis Areas of Dental Panoramic X-ray Images Radiological Physics and Technology │ Radiological Physics and Technology │ 15,pp.170-176 (Co-authored)
4.	2022/04	Semiautomated Segmentation and Volume Measurements of Cervical Carotid High-Signal Plaques Using 3D Turbo Spin-Echo T1-Weighted Black-Blood Vessel Wall Imaging: A Preliminary Study │ Diagnostics │ 12 (4) (Co-authored)
5.	2022/04	Tumor blood flow and apparent diffusion coefficient histogram analysis for differentiating malignant salivary tumors from pleomorphic adenomas and Warthin’s tumors │ Scientific Reports │ 12,pp.1-10 (Co-authored)
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Academic conference presentation
1.	2023/01	Computerized classification method for molecular subtypes of low-grade glioma in brain MRI images using 3D-attention branch networks with additive angular margin penalty (2023 INTERNATIONAL WORKSHOP ON ADVANCED IMAGE TECHNOLOGY)
2.	2022/12	Anomaly Detection for Lung CT image Using Efficient GAN with Learning Stabilizations (SCIS&ISIS2022)
3.	2022/10	Anomaly Detection for Lung CT Images Using SVDD-AE (2022 IEEE 11th Global Conference on Consumer Electronics (GCCE))
4.	2020/05	Computerized classification scheme for distinguishing between benign and malignant masses by analyzing multiple MRI sequences with convolutional neural network (16th International Workshop on Breast Imaging)
5.	2020/05	Computerized determination scheme for histological classification of masses on breast ultrasonographic images using combination of CNN features and morphologic features (16th International Workshop on Breast Imaging)
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Winning science prize
1.	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)
2.	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)
3.	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)
4.	2018/03	Symposium Neuroradiologicum 2018 Cum Laude (Clinical applications and usefulness of pseudocontinuous arterial spin labeling in head and neck entities)
5.	2012/10	Fourth International Workshop on Regional Innovation Studies - Biomedical Engineering -. Outstanding Paper Award. (Computer-aided Diagnosis Scheme for Determining Histological Classification of Breast Masses Using Clinical Features and Texture Features.)
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Grants-in-Aid for Scientific Research -KAKENHI-
1.	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)
2.	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)
3.	2020/04 ～ 2023/03	Establishment of non-invasive image assessment method for early detection and therapeutic effect determination of pulmonary hypertension by ultra-high-resolution computed tomography │ Grant-in-Aid for Scientific Research(C)
4.	2018/04 ～ 2021/03	Prediction of FFR from coronary MRA using deep learning │ Grant-in-Aid for Scientific Research(C)
5.	2017/04 ～ 2020/03	Development of comprehensive diagnostic method, combining the assessment of liver perfusion and the assessment of hepatic cellular function, for predicting the liver function after hepatectomy │ Grant-in-Aid for Scientific Research(C)

External Researcher ID
ORCID ID
0000-0003-0181-7496