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Paper Abstract and Keywords
Presentation 2020-10-09 11:00
Examination of data preprocessing in functional MRI image analysis using CNN
Yuta Hosoi (Niigata Univ.), Takafumi Hayashi (Nihon Univ) PRMU2020-22
Abstract (in Japanese) (See Japanese page) 
(in English) fuctional MRI(fMRI) has been used in various fields from medicine and neuroscience to psychology andlinguistics since its introduction in the 1990s. Among non-invasive brain measuring instruments, fMRI has excellent spatial resolution, which greatly contributes to the identification of brain function and the estimation of mental illness.It is said that fMRI images contain a lot of information, and with the progress of computer science, analysis methods are diversifying.In recent years, with the advent of deep learning, which is a type of AI, research on analysis methods using deep learning has been actively conducted.In particular, the number of analyzes using convolutional neural networks (CNNs) is increasing, and in previous studies, fMRI images were classified by 3D-CNN. However, the image obtained from fMRI contains noise and parts that do not contribute to analysis, and CNN is susceptible to noise, so appropriate pretreatment is required. Therefore, in this study, we will confirm how the learning result changes by the skull fragment that removes the skull shown in the image and the normalization process that unifies the structure of the brain. We also use Grad-CAM, a feature visualization technique, to report the effects of the skull and its surroundings.
Keyword (in Japanese) (See Japanese page) 
(in English) functional MRI / Convolutional Neural Network(CNN) / Grad-CAM / Preprocessing / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 187, PRMU2020-22, pp. 20-25, Oct. 2020.
Paper # PRMU2020-22 
Date of Issue 2020-10-02 (PRMU) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF PRMU2020-22

Conference Information
Committee PRMU  
Conference Date 2020-10-09 - 2020-10-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Recognition and understating of human 
Paper Information
Registration To PRMU 
Conference Code 2020-10-PRMU 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Examination of data preprocessing in functional MRI image analysis using CNN 
Sub Title (in English)  
Keyword(1) functional MRI  
Keyword(2) Convolutional Neural Network(CNN)  
Keyword(3) Grad-CAM  
Keyword(4) Preprocessing  
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Keyword(6)  
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Keyword(8)  
1st Author's Name Yuta Hosoi  
1st Author's Affiliation Niigata University (Niigata Univ.)
2nd Author's Name Takafumi Hayashi  
2nd Author's Affiliation College of Engineering. Nihon University (Nihon Univ)
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Speaker Author-1 
Date Time 2020-10-09 11:00:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2020-22 
Volume (vol) vol.120 
Number (no) no.187 
Page pp.20-25 
#Pages 6 
Date of Issue 2020-10-02 (PRMU) 

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