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Paper Abstract and Keywords
Presentation 2021-07-16 14:00
Image Quality Improvements Using Half Fourier Encoding Method and Non-random Signal Under-sampling in CS-MRI Deep Learning Reconstruction
Yuta Miyamoto, Satoshi Ito (Utsunomiya Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Compressed Sensing has the potential to reduce the scan time of MRI, and recently, deep learning has attract at tensions for reconstructing high quality images. In the application of CS to MR imaging, data acquisition points are skipped randomly in signal space. Generally, image quality improves in proportion to the sampling density of signal. Half Fourier imaging (HF) is well-known MR fast imaging method in which almost half of the signal in signal space are acquired. When CS is combined with HF, image quality improvement is expected with the increase of the sampling density which is achieved by acquiring a given number of signals on one side of the signal space. In this study, we discuss the image quality obtained in deep learning reconstruction for CS with HF using random or regular under-sampling patterns. It was shown that higher quality images were obtained when HF were combined with CS and regular under-sampling patterns were used.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / Compressed Sensing / Half Fourier Encoding / MRI / / / /  
Reference Info. ITE Tech. Rep., vol. 45, no. 18, ME2021-63, pp. 9-11, July 2021.
Paper # ME2021-63 
Date of Issue 2021-07-09 (ME) 
ISSN Print edition: ISSN 1342-6893    Online edition: ISSN 2424-1970
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Conference Information
Committee ME  
Conference Date 2021-07-16 - 2021-07-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ME 
Conference Code 2021-07-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Image Quality Improvements Using Half Fourier Encoding Method and Non-random Signal Under-sampling in CS-MRI Deep Learning Reconstruction 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) Compressed Sensing  
Keyword(3) Half Fourier Encoding  
Keyword(4) MRI  
1st Author's Name Yuta Miyamoto  
1st Author's Affiliation Utsunomiya University (Utsunomiya Univ.)
2nd Author's Name Satoshi Ito  
2nd Author's Affiliation Utsunomiya University (Utsunomiya Univ.)
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Speaker Author-1 
Date Time 2021-07-16 14:00:00 
Presentation Time 30 minutes 
Registration for ME 
Paper # ME2021-63 
Volume (vol) vol.45 
Number (no) no.18 
Page pp.9-11 
Date of Issue 2021-07-09 (ME) 

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