Paper Abstract and Keywords |
Presentation |
2018-03-20 09:45
[Short Paper]
Prostate Zonal Segmentation Using Deep Learning Changhee Han, Jin Zhang, Ryuichiro Hataya, Yudai Nagano, Hideki Nakayama (Univ. of Tokyo), Leonardo Rundo (Milano-Bicocca Univ.) MI2017-86 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Prostate cancer is the second most common cancer among men and segmenting the Transition Zone (TZ) and Peripheral Zone (PZ) of the prostate is clinically essential as the frequency and severity of tumors can differ in these zones; however, the boundary of them are unclear. Therefore, we automatically segment those zones on T2-weighted Magnetic Resonance (MR) images using deep learning. Here, we use two different prostate datasets to confirm the influence of concatenating different datasets towards better clinical diagnosis. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Prostate Zonal Segmentation / Deep Learning / SegNet / MRI / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 518, MI2017-86, pp. 69-70, March 2018. |
Paper # |
MI2017-86 |
Date of Issue |
2018-03-12 (MI) |
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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MI2017-86 |
Conference Information |
Committee |
SIP EA SP MI |
Conference Date |
2018-03-19 - 2018-03-20 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
|
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics [SIP, EA, SP]/ Medical Image Engineering, Analysis, Recognition, etc. [MI] |
Paper Information |
Registration To |
MI |
Conference Code |
2018-03-SIP-EA-SP-MI |
Language |
English |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Prostate Zonal Segmentation Using Deep Learning |
Sub Title (in English) |
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Keyword(1) |
Prostate Zonal Segmentation |
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Deep Learning |
Keyword(3) |
SegNet |
Keyword(4) |
MRI |
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1st Author's Name |
Changhee Han |
1st Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
2nd Author's Name |
Jin Zhang |
2nd Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
3rd Author's Name |
Ryuichiro Hataya |
3rd Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
4th Author's Name |
Yudai Nagano |
4th Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
5th Author's Name |
Hideki Nakayama |
5th Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
6th Author's Name |
Leonardo Rundo |
6th Author's Affiliation |
Milano-Bicocca University (Milano-Bicocca Univ.) |
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Speaker |
Author-1 |
Date Time |
2018-03-20 09:45:00 |
Presentation Time |
15 minutes |
Registration for |
MI |
Paper # |
MI2017-86 |
Volume (vol) |
vol.117 |
Number (no) |
no.518 |
Page |
pp.69-70 |
#Pages |
2 |
Date of Issue |
2018-03-12 (MI) |
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