Oral

Oral
AI/Machine learning

Sat. Sep 11, 2021 10:30 AM - 11:30 AM Room 5 (PACIFICO Yokohama North, 3F, G316+317)

Chairs: Daisuke Hirahara（Harada Academy）, Yasuhiko Tachibana（Quantum-medicine AI Research Group, QST）

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[O2-059] Model-based deep learning reconstruction using folded image training strategy (FITS) for abdominal 3D T1-weighted images

^○Satoshi Funayama¹, Utaroh Motosugi², Shintaro Ichikawa³, Hiroyuki Morisaka¹, Yoshie Omiya¹, Hiroshi Onishi¹ (1.Department of Radiology, University of Yamanashi, 2.Department of Radiology, Kofu-Kyoritsu Hospital, 3.Department of Radiology, Hamamatsu University School of Medicine)

[O2-060] Initial investigation of machine learning-based MRCP plane detection method toward to the slice positioning support function for liver MRI

^○Yutaka Hoshiyama¹, Hong Yang², Chunqi Wang², Zhen Zhou², Kensuke Shinoda¹ (1.MRI Systems Division, Canon Medical Systems Corporation, 2.Research & Development Center, Canon Medical Systems (China) Co., Ltd)

[O2-061] Comparison of 3D MRCPs among PI, CS and Fast 3D Mode Multiple with and without DLR in IPMN Patients

^○Takahiro Matsuyama¹, Yoshiharu Ohno^1,2, Kaori Yamamoto³, Masato Ikedo³, Masao Yui³, Akiyoshi Iwase⁴, Takashi Fukuba⁴, Satomu Hanamatsu¹, Yuki Obama¹, Takahiro Ueda¹, Hirotaka Ikeda¹, Kazuhiro Murayama², Kazuhiro Katada¹, Shigeki Kobayashi⁵, Hiroshi Toyama¹ (1.Department of Radiology, Fujita Health University School of Medicine, 2.Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, 3.Canon Medical Systems Corporation, 4.Department of Radiology, Fujita Health University Hospital, 5.Faculty of Radiological Technology, Fujita Health University, School of Medical Sciences)

[O2-062] Impact of Deep Learning on Prostate T2-weighted Images

^○Ryosuke Fujii¹, Yuki Takayanagi¹, Wakaba Koide¹, Masayoshi Sugimura¹, Takayuki Masui² (1.Seirei Hamamatsu General Hospital Radiation part, 2.Seirei Hamamatsu General Hospital Department of Radiology)

[O2-063] Deep Learning Reconstruction of PROPELLER T2 weighted imaging of the Prostate for PI-RADS Protocol

^○Takayuki Masui¹, Mitsuharu Miyoshi², Yuji Iwadate², Motoyuki Katayama¹, Masako Sasaki¹, Takahiro Yamada¹, Naoto Kono¹, Xinzeng Wang³, Ersin Bayram³, Yuki Takayanagi¹ (1.Department of Radiology, Seirei Hamamatsu General Hospital, 2.Global MR Applications and Workflow, GE Healthcare Japan, 3.Global MR Applications and Workflow, GE Healthcare)

[O2-064] Capability of Compressed Sensing and Deep Learning Reconstruction on Women's Pelvic MRI at 1.5-T MR System as Compared with Parallel Imaging

^○Takahiro Ueda¹, Yoshiharu Ohno¹, Kaori Yamamoto², Natsuka Yazawa², Ikki Tozawa³, Masayuki Sato³, Motohiro Katagiri³, Masato Ikedo², Masao Yui², Kazuhiro Murayama⁴, Kazuhiro Katada¹, Shigeki Kobayashi⁵, Hiroshi Toyama¹ (1.Department of Radiology, Fujita Health University School of Medicine, 2.Canon Medical Systems Corporation, 3.Department of Radiology, Fujita Health University Bantane Hospital, 4.Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, 5.Faculty of Radiological Technology, Fujita Health University School of Medical Sciences)