Brain4

Technology

2022年9月11日(日) 08:00 〜 20:00 現地会場なし (配信のみ)

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[WP-17-1] Automatic striatal region setting method on magnetic resonance images for a 123I-FP-CIT quantification method using deep convolutional neural network

Kaito Ozaki¹、Yoshikazu Uchiyama⁴、Ryosuke Kamezaki²、Retsu Kawazoe¹、Shinya Shiraishi³、Shigeki Ito⁴ (1.Graduate School of Health Science, Kumamoto University、2.Division of Radiology, Department of Medical Technology, Kumamoto University Hospital、3.Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University、4.Department of Medical Radiation Sciences, Faculty of Life Sciences, Kumamoto University)

[WP-17-2] Brain positron emission tomography attenuation correction method using synthetic computed tomography images based on magnetic resonance with a deep convolutional neural network

Retsu Kawazoe¹、Yoshikazu Uchiyama⁴、Ryosuke Kamezaki²、Ryuji Ikeda²、Shinya Shiraishi³、Shigeki Ito⁴ (1.Graduate School of Health Sciences, Kumamoto University、2.Division of Radiology, Department of Medical Technology, Kumamoto University Hospital 、3.Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University、4.Department of Medical Radiation Sciences, Faculty of Life Sciences, Kumamoto University)

[WP-17-3] Spatial normalization of brain FDG images with high-resolution digital PET system: effect of different processing strategies

Masanobu Ibaraki、Yuki Shinohara、Keisuke Matsubara、Kaoru Sato、Hiroyuki Yamamoto、Toshibumi Kinoshita (Akita Research Institute of Brain and Blood Vessels)

[WP-17-4] Evaluation on Applicability of Generative Adversarial Network to Synthesize Training Images for AI-Based Computer Aided Diagnostic Algorithm to Dementia

Aya Watanabe¹、Takahiro Yamada²、Takashi Nagaoka³、Mitsutaka Nemoto⁴、Hiroshi Watabe⁵、Masanobu Ibaraki⁶、Keisuke Matsubara⁷、Kohei Hanaoka²、Kazunari Ishii^2,8、Yuichi Kimura¹ (1.Graduate School of Science and Engineering, Kindai University, Osaka, Japan、2.Division of PET Molecular Imaging, Kindai University Hospital、3.Graduate School of Biology-Oriented Science and Technology, Kindai University、4.Faculty of Biology-Oriented Science and Technology, Kindai University、5.Cyclotron and Radioisotope Center (CYRIC), Tohoku University、6.Department of Radiology and Nuclear Medicine, Research Institute for Brain and Blood Vessels, Akita Cerebrospinal and Cardiovascular Center、7.Department of Management Science and Engineering, Faculty of System science and Technology, Akita Prefectural University、8.Department of Radiology, Faculty of Medicine, Kindai University)

[WP-17-5] Partial volume effect correction in brain 18F-FDG PET images using CT images and construction of a database of normal subjects and evaluation of age-related metabolic changes.

Fumiya Onoue¹、Shinya Yamamoto²、Hideaki Uozumi²、Daichi Uchida³、Ryousuke Kamezaki⁴、Yuuya Nakamura⁴、Ryuji Ikeda⁴、Shinya Shiraishi⁵、Seiji Tomiguchi⁶、Fumi Sakamoto^5,7 (1.Graduate School of Health Sciences, Kumamoto University、2.Uozumi Clinic、3.Kumamoto Radiosurgery Clinic、4.Division of Radiology, Department of Medical Technology, Kumamoto University Hospital、5.Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University、6.Japanese Red Cross Kumamoto Health Care Center、7.Department of Medical Radiation Sciences, Faculty of Life Sciences, Kumamoto University)

[WP-17-6] A Novel Method to Determine PET Parameters for Partial Volume Effect Correction Based Only on Individual Brain Images, Not on Phantom Experiments.

Akira Arai^1,2 (1.Kousei Sendai Clinic、2.Sendai Seiryo Clinic)