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Paper Abstract and Keywords
Presentation 2025-02-22 11:00
Performance evaluation of Deep Learning based Image Reconstruction Models in Holographic MR Simultaneous Multi-slice Imaging
Haruki Takeichi, Masaki Furuta, Kazuki Yamato, Satoshi Ito (Utsunomiya Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) This study investigated a reconstruction model and a deep learning architecture to improve the quality of reconstructed images in a MRI simultaneous multi-slice imaging based on holography principles. We used U-Net, SARA-GAN, and SwinMR as deep learning architectures, adding 3D image models to traditional 2D cross-sectional images. Simulation experiments showed that the image quality obtained with the 3D image model and SARA-GAN exceeded those of the conventional method in terms of PSNR and LPIPS under conditions with a sufficient number of training cycles.
Keyword (in Japanese) (See Japanese page) 
(in English) MRI / Simultaneous Multi-slice imaging / fast imaging / CNN / holography / / /  
Reference Info. ITE Tech. Rep., vol. 49, no. 7, ME2025-45, pp. 17-20, Feb. 2025.
Paper # ME2025-45 
Date of Issue 2025-02-15 (ME) 
ISSN Online edition: ISSN 2424-1970
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Conference Information
Committee ME  
Conference Date 2025-02-22 - 2025-02-22 
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 2025-02-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance evaluation of Deep Learning based Image Reconstruction Models in Holographic MR Simultaneous Multi-slice Imaging 
Sub Title (in English)  
Keyword(1) MRI  
Keyword(2) Simultaneous Multi-slice imaging  
Keyword(3) fast imaging  
Keyword(4) CNN  
Keyword(5) holography  
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Keyword(7)  
Keyword(8)  
1st Author's Name Haruki Takeichi  
1st Author's Affiliation Utsunomiya University (Utsunomiya Univ.)
2nd Author's Name Masaki Furuta  
2nd Author's Affiliation Utsunomiya University (Utsunomiya Univ.)
3rd Author's Name Kazuki Yamato  
3rd Author's Affiliation Utsunomiya University (Utsunomiya Univ.)
4th Author's Name Satoshi Ito  
4th Author's Affiliation Utsunomiya University (Utsunomiya Univ.)
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Speaker Author-1 
Date Time 2025-02-22 11:00:00 
Presentation Time 15 minutes 
Registration for ME 
Paper # ME2025-45 
Volume (vol) vol.49 
Number (no) no.7 
Page pp.17-20 
#Pages
Date of Issue 2025-02-15 (ME) 


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