Presentation 2022-01-24
Reduction of Truncation Artifacts by Massive-Training Artificial Neural Network (MTANN) in Fast-Acquisition MRI of the Knee
Maodong Xiang, Ze Jin, Kenji Suzuki,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English)
Keyword(in Japanese) (See Japanese page)
Keyword(in English)
Paper # IE2021-31
Date of Issue 2022-01-17 (IE)

Conference Information
Committee IE
Conference Date 2022/1/24(1days)
Place (in Japanese) (See Japanese page)
Place (in English) National Institute of Informatics
Topics (in Japanese) (See Japanese page)
Topics (in English) Image Processing, Image Coding, etc.
Chair Kazuya Kodama(NII)
Vice Chair Hiroyuki Bandoh(NTT) / Toshihiko Yamazaki(Univ. of Tokyo)
Secretary Hiroyuki Bandoh(KDDI Research) / Toshihiko Yamazaki(Nagoya Inst. of Tech.)
Assistant Shunsuke Iwamura(NHK) / Shinobu Kudo(NTT)

Paper Information
Registration To Technical Committee on Image Engineering
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Reduction of Truncation Artifacts by Massive-Training Artificial Neural Network (MTANN) in Fast-Acquisition MRI of the Knee
Sub Title (in English)
Keyword(1)
1st Author's Name Maodong Xiang
1st Author's Affiliation Tokyo Institute of Technology(Tokyo Tech)
2nd Author's Name Ze Jin
2nd Author's Affiliation Tokyo Institute of Technology(Tokyo Tech)
3rd Author's Name Kenji Suzuki
3rd Author's Affiliation Tokyo Institute of Technology(Tokyo Tech)
Date 2022-01-24
Paper # IE2021-31
Volume (vol) vol.121
Number (no) IE-346
Page pp.pp.21-26(IE),
#Pages 6
Date of Issue 2022-01-17 (IE)