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Paper Abstract and Keywords
Presentation 2022-05-20 16:00
Application of LambdaNetwork learning long-range interactions between pixels to metal artifact detection
Daisuke Shigemori, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Although deep learning-based image transformation has been attempted to be applied to metal artifact reduction, feature extraction based on the relationship between distant pixels is considered to be more effective in detecting artifacts that exist over a wide area. In this study, metal artifact detection was performed using a region extraction model applying a LambdaNetwork. A quantitative evaluation of detection accuracy was attempted by creating a dataset containing labeled images showing areas affected by artifacts. The detection accuracy of the proposed method and conventional methods are compared, and the effectiveness of the LambdaNetwork is verified.
Keyword (in Japanese) (See Japanese page) 
(in English) Self-Attention / U-net / Metal artifact detection / / / / /  
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Conference Information
Committee IEICE-SIP IEICE-BioX IEICE-IE IEICE-MI IST ME  
Conference Date 2022-05-19 - 2022-05-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Kumamoto University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IEICE-MI 
Conference Code 2022-05-SIP-BioX-IE-MI-IST-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Application of LambdaNetwork learning long-range interactions between pixels to metal artifact detection 
Sub Title (in English)  
Keyword(1) Self-Attention  
Keyword(2) U-net  
Keyword(3) Metal artifact detection  
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1st Author's Name Daisuke Shigemori  
1st Author's Affiliation Kyoto University (Kyoto Univ.)
2nd Author's Name Megumi Nakao  
2nd Author's Affiliation Kyoto University (Kyoto Univ.)
3rd Author's Name Tetsuya Matsuda  
3rd Author's Affiliation Kyoto University (Kyoto Univ.)
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Speaker Author-1 
Date Time 2022-05-20 16:00:00 
Presentation Time 20 minutes 
Registration for IEICE-MI 
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Volume (vol) vol.46 
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