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| Presentation | 2023-03-06 15:34 Reproducing method of cancer annotation by local features in pathological images Shunya Mutsuda (KIT), Sohsuke Yamada (Kanazawa Medical Univ.), Toshiki Kindo (KIT)  MI2022-90 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In recent years, AI-based pathological image diagnosis technology has been actively researched. Therefore, in this study, we propose a pathological image diagnosis technique based on the information density method, which does not require boundary line information between cancer and normal, and has a clear feature quantity that serves as a basis for distinguishing between the two. When this method was applied to the pathological image data of CAMELYON 16, an international competition for artificial intelligence pathological diagnosis, it was possible to reproduce the correct boundary line with high accuracy. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Local Feature / Information Density / Border / Visualization Of Information Density / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 417, MI2022-90, pp. 82-87, March 2023. | |
| Paper # | MI2022-90 | |
| 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) | |
| Download PDF | MI2022-90 |
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| 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) | |
| 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) | Reproducing method of cancer annotation by local features in pathological images |
| Sub Title (in English) | |
| Keyword(1) | Local Feature |
| Keyword(2) | Information Density |
| Keyword(3) | Border |
| Keyword(4) | Visualization Of Information Density |
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| 1st Author's Name | Shunya Mutsuda |
| 1st Author's Affiliation | Kanazawa Institute of Technology (KIT) |
| 2nd Author's Name | Sohsuke Yamada |
| 2nd Author's Affiliation | Kanazawa Medical University (Kanazawa Medical Univ.) |
| 3rd Author's Name | Toshiki Kindo |
| 3rd Author's Affiliation | Kanazawa Institute of Technology (KIT) |
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| Speaker | Author-1 |
| Date Time | 2023-03-06 15:34:00 |
| Presentation Time | 13 minutes |
| Registration for | MI |
| Paper # | MI2022-90 |
| Volume (vol) | vol.122 |
| Number (no) | no.417 |
| Page | pp.82-87 |
| #Pages | 6 |
| Date of Issue | 2023-02-27 (MI) |
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