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| Presentation | 2023-03-07 17:29 [Short Paper] High Accuracy Segmentation of trachea and bronchus using 3D U-Net Tatsuya Ogasa, Rikuto Kuroda, Yoshiki Kawata, Hidenobu Suzuki (Tokushima Univ), Yuzi Matsumoto, Takaki Tsuchida, Masahiko Kusumoto (NCC), Noboru Niki (Medical Science Institute Inc.)  MI2022-128 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | High-Accuracy trachea and bronchus segmentation is required for lymph node analysis in lung cancer. Since manual segmentation is time-consuming, highly accurate automatic trachea and bronchus segmentation is required. In this paper, Res3D U-Net is used to segmentation trachea, bronchus, and lymph nodes from 3D CT images. The labels of trachea, bronchus, and lymph nodes for training are created in two steps in a human-in-the-loop workflow to improve efficiency. Next, the training data is used to train Res3D U-Net, and the automatic segmentation results are evaluated to demonstrate the effectiveness of the training data creation method. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | airway / lymph-node / segmentation / deep learning / U-Net / Human-in-the-loop / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 417, MI2022-128, pp. 217-220, March 2023. | |
| Paper # | MI2022-128 | |
| 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 | MI2022-128 |
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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) | High Accuracy Segmentation of trachea and bronchus using 3D U-Net |
| Sub Title (in English) | |
| Keyword(1) | airway |
| Keyword(2) | lymph-node |
| Keyword(3) | segmentation |
| Keyword(4) | deep learning |
| Keyword(5) | U-Net |
| Keyword(6) | Human-in-the-loop |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Tatsuya Ogasa |
| 1st Author's Affiliation | Tokushima University (Tokushima Univ) |
| 2nd Author's Name | Rikuto Kuroda |
| 2nd Author's Affiliation | Tokushima University (Tokushima Univ) |
| 3rd Author's Name | Yoshiki Kawata |
| 3rd Author's Affiliation | Tokushima University (Tokushima Univ) |
| 4th Author's Name | Hidenobu Suzuki |
| 4th Author's Affiliation | Tokushima University (Tokushima Univ) |
| 5th Author's Name | Yuzi Matsumoto |
| 5th Author's Affiliation | National Cancer Center Hospital (NCC) |
| 6th Author's Name | Takaki Tsuchida |
| 6th Author's Affiliation | National Cancer Center Hospital (NCC) |
| 7th Author's Name | Masahiko Kusumoto |
| 7th Author's Affiliation | National Cancer Center Hospital (NCC) |
| 8th Author's Name | Noboru Niki |
| 8th Author's Affiliation | Medical Science Institute Inc. (Medical Science Institute Inc.) |
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| Speaker | Author-1 |
| Date Time | 2023-03-07 17:29:00 |
| Presentation Time | 13 minutes |
| Registration for | MI |
| Paper # | MI2022-128 |
| Volume (vol) | vol.122 |
| Number (no) | no.417 |
| Page | pp.217-220 |
| #Pages | 4 |
| Date of Issue | 2023-02-27 (MI) |
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