Paper Abstract and Keywords |
Presentation |
2023-01-17 09:50
Oral Cytology Based on Representation Learning of Visually Salient Cells Kazuki Matsuo, Eiji Mitate, Tomoya Sakai (Nagasaki Univ.) MICT2022-44 MBE2022-44 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
We classify microscopically photographed cells for screening tests to find oral cancer in its early stages. Oral cancer is one of the most common malignancies and has a relatively high mortality rate. Early detection and diagnosis are very important to improve the survival rate.. Automatic classification of oral cells is required as a simple and early screening. Deep learning-based cell image classification tend to focus on the background rather than the cells because background is dominant. Cells are salient in images. We propose a representation learning that encourages a convolutional autoencoder to focus on salient cell regions. The trained encoder is applicable to automatic classification of oral cells. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
saliency map / convolutional autoencoder / deep learning / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 334, MICT2022-44, pp. 7-12, Jan. 2023. |
Paper # |
MICT2022-44 |
Date of Issue |
2023-01-10 (MICT, MBE) |
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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MICT2022-44 MBE2022-44 |
Conference Information |
Committee |
MBE MICT IEE-MBE |
Conference Date |
2023-01-17 - 2023-01-17 |
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(See Japanese page) |
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Paper Information |
Registration To |
MICT |
Conference Code |
2023-01-MBE-MICT-MBE |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
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(See Japanese page) |
Title (in English) |
Oral Cytology Based on Representation Learning of Visually Salient Cells |
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saliency map |
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convolutional autoencoder |
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deep learning |
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1st Author's Name |
Kazuki Matsuo |
1st Author's Affiliation |
Nagasaki University (Nagasaki Univ.) |
2nd Author's Name |
Eiji Mitate |
2nd Author's Affiliation |
Nagasaki University (Nagasaki Univ.) |
3rd Author's Name |
Tomoya Sakai |
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Nagasaki University (Nagasaki Univ.) |
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Speaker |
Author-1 |
Date Time |
2023-01-17 09:50:00 |
Presentation Time |
25 minutes |
Registration for |
MICT |
Paper # |
MICT2022-44, MBE2022-44 |
Volume (vol) |
vol.122 |
Number (no) |
no.334(MICT), no.335(MBE) |
Page |
pp.7-12 |
#Pages |
6 |
Date of Issue |
2023-01-10 (MICT, MBE) |
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