Poster Session

Poster Session
AI1

Fri. Sep 22, 2023 2:40 PM - 3:40 PM Poster 1 (Karuizawa Prince Hotel West, Asama International Conference Hall A-E)

Chairs: Tetsuya Wakayama（GE HealthCare）, Tsuyoshi Ueyama（The University of Tokyo Hospital）

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[PS03-1] Comparison of 1.5T and 3T MRA for detecting cerebral aneurysms using deep learning-based computer-assisted detection (CAD) software

Taku Tajima^1,2, Hiroyuki Akai³, Koichiro Yasaka⁴, Akira Kunimatsu¹, Naoki Yoshioka², Masaaki Akahane², Kuni Ohtomo⁵, Osamu Abe⁴, Shigeru Kiryu² (1.Department of Radiology, International University of Health and Welfare Mita Hospital, 2.Department of Radiology, International University of Health and Welfare Narita Hospital, 3.Department of Radiology, The Institute of Medical Science, The University of Tokyo, 4.Department of Radiology, Graduate School of Medicine, The University of Tokyo, 5.International University of Health and Welfare)

[PS03-2] Improving generalizability of machine learning image recognition models by reducing image feature differences in brain diffusion MRI.

Akihiko Wada, Toshiaki Akashi, Yujiro Otsuka, Kanako Sato, Nobuo Tomizawa, Akifumi Hagiwara, Junko Kikuta, Koji Kamagata, Katsuhiro Sano, Kanako Kumamaru, Atsushi Nakanishi, Shigeki Aoki (Department of Radiology, Juntendo University School of Medicine)

[PS03-3] Effectiveness of brain T1/T2-weighted images for automatic detection of perivascular space using the deep learning model

Sen Guo, Junko Kikuta, Koji Kamagata, Hongkai Chen, Yuya Saito, Kaito Takabayashi, Wataru Uchida, Yujiro Otsuka, Yayoi Hayakawa, Akihiko Wada, Shigeki Aoki (Department of Radiology, Juntendo University Graduate School of Medicine)

[PS03-4] Quantitative Evaluation of High-Resolution Deep Learning Reconstruction (HR-DLR) with Respect to Sharpness Improvement and Gibbs-Artifact Reduction.

Ryutaro Yano, Hideaki Kutsuna, Shun Uematsu, Kensuke Shinoda (Canon Medical Systems Corporation)

[PS03-5] Improvement of MR Imaging-Instruction Prediction Model Using Task Adaptive Pre-Training

Kozo Shimizu¹, Yuya Yamatani¹, Tetsuya Tachiiri², Yoshimasa Mai¹, Nagaaki Marugami² (1.Central Division of Radiology, Nara Medical University Hospital, 2.Department of Diagnostic and Interventional Radiology, Nara Medical University)

[PS03-6] Image reconstruction for PROPELLER MRI by combining deep learning and blade images

Shun Kato (Graduate School of Health Sciences, Kyorin University)

[PS03-7] Investigation of the properties of deep learning image reconstruction using super-resolution

Hiroyuki Hoshiko, Masaaki Ninomiya, Akiyoshi Yamamoto (Social Medical Corporation Kyoaikai Tobata Kyoritsu Hospital, Diagnostic Imaging Center)