Paper Abstract and Keywords |
Presentation |
2010-02-16 10:50
Detection of Abnormality in Brain using Structural Features on Phase Images of Super-low Field MRI Yuko Ouchi, Ikuko Uwano, Masashi Kameda (Iwate Pref. Univ.), Shunrou Fujiwara (Iwate Med. Univ.) ITS2009-74 IE2009-168 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In our study, we have proposed a new MRI device to find out any brain diseases even if people don’t come to hospital. The output of the proposed device is a set of super-low field MR images which are indistinct in comparison with the previous MR images. Therefore, it is difficult to detect brain diseases from the super-low field MR images by the conventional detection measures. This paper presents a method to detect abnormality from the super-low field brain MR images of patients. Usually, super-low field magnitude images have been used to detect any abnormality in the brain. However, the detection of abnormality in the brain has been difficult at the complicated structure area such as the sulcus. In order to solve the problem, we have focused on phase images. In the proposed method, the subband to detect the abnormality easily is determined by partitioning the super-low field phase images into some subbands, and the detection method is developed for the obtained subband phase images. It is seen in our experiments that the abnormality in the brain is distinguished using both results of super-low field magnitude images and super-low field phase images. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Brain / Super-low Field MR Images / Abnormality Detection / Magnitude Images / Phase Images / / / |
Reference Info. |
IEICE Tech. Rep., vol. 109, no. 415, IE2009-168, pp. 209-214, Feb. 2010. |
Paper # |
IE2009-168 |
Date of Issue |
2010-02-08 (ITS, IE) |
ISSN |
Print edition: ISSN 0913-5685 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) |
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ITS2009-74 IE2009-168 |
Conference Information |
Committee |
ITE-AIT IE ITE-HI ITE-ME ITS |
Conference Date |
2010-02-15 - 2010-02-16 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Graduate School of Information and Technology, Hokkaido Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
IE |
Conference Code |
2010-02-AIT-IE-HI-ME-ITS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Detection of Abnormality in Brain using Structural Features on Phase Images of Super-low Field MRI |
Sub Title (in English) |
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Keyword(1) |
Brain |
Keyword(2) |
Super-low Field MR Images |
Keyword(3) |
Abnormality Detection |
Keyword(4) |
Magnitude Images |
Keyword(5) |
Phase Images |
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1st Author's Name |
Yuko Ouchi |
1st Author's Affiliation |
Iwate Prefectural University (Iwate Pref. Univ.) |
2nd Author's Name |
Ikuko Uwano |
2nd Author's Affiliation |
Iwate Prefectural University (Iwate Pref. Univ.) |
3rd Author's Name |
Masashi Kameda |
3rd Author's Affiliation |
Iwate Prefectural University (Iwate Pref. Univ.) |
4th Author's Name |
Shunrou Fujiwara |
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Iwate Medical University (Iwate Med. Univ.) |
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Speaker |
Author-1 |
Date Time |
2010-02-16 10:50:00 |
Presentation Time |
25 minutes |
Registration for |
IE |
Paper # |
ITS2009-74, IE2009-168 |
Volume (vol) |
vol.109 |
Number (no) |
no.414(ITS), no.415(IE) |
Page |
pp.209-214 |
#Pages |
6 |
Date of Issue |
2010-02-08 (ITS, IE) |
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