Paper Abstract and Keywords |
Presentation |
2023-03-06 09:57
Multi-label multi-class estimation of pathology in high-resolution chest CT images using SRGAN Tetsuya Asakawa, Riku Tsuneda, Yuki Sugimoto (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) MI2022-76 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The purpose of this research, three pathologies (thickening, calcification, and cavitation) were accurately estimated as a multi-label problem from 3D chest CT data of tuberculosis patients. We extracted 2D image data of only the lung (excluding space, fat, bone, etc.) from the 3D chest CT data of a tuberculosis patient, and generated super-resolution images of the CT image using SRGAN. We developed a unique model that combined features using three DNN models using the whole CT image and the disease-only image. As a result, the average AUC was 0.658 for EfficientNetB07. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Computed Tomography / Tuberculosis / Deep Learning / Nulti-label classification / Super-resolution / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 417, MI2022-76, pp. 14-19, March 2023. |
Paper # |
MI2022-76 |
Date of Issue |
2023-02-27 (MI) |
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) |
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MI2022-76 |
Conference Information |
Committee |
MI |
Conference Date |
2023-03-06 - 2023-03-07 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
OKINAWA SEINENKAIKAN |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
MI |
Conference Code |
2023-03-MI |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Multi-label multi-class estimation of pathology in high-resolution chest CT images using SRGAN |
Sub Title (in English) |
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Keyword(1) |
Computed Tomography |
Keyword(2) |
Tuberculosis |
Keyword(3) |
Deep Learning |
Keyword(4) |
Nulti-label classification |
Keyword(5) |
Super-resolution |
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1st Author's Name |
Tetsuya Asakawa |
1st Author's Affiliation |
Toyohashi University of Technology (TUT) |
2nd Author's Name |
Riku Tsuneda |
2nd Author's Affiliation |
Toyohashi University of Technology (TUT) |
3rd Author's Name |
Yuki Sugimoto |
3rd Author's Affiliation |
Toyohashi University of Technology (TUT) |
4th Author's Name |
Kazuki Shimizu |
4th Author's Affiliation |
Toyohashi Heart Center (THC) |
5th Author's Name |
Takuyuki Komoda |
5th Author's Affiliation |
Toyohashi Heart Center (THC) |
6th Author's Name |
Masaki Aono |
6th Author's Affiliation |
Toyohashi University of Technology (TUT) |
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Speaker |
Author-1 |
Date Time |
2023-03-06 09:57:00 |
Presentation Time |
13 minutes |
Registration for |
MI |
Paper # |
MI2022-76 |
Volume (vol) |
vol.122 |
Number (no) |
no.417 |
Page |
pp.14-19 |
#Pages |
6 |
Date of Issue |
2023-02-27 (MI) |
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