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| Presentation | 2021-11-05 15:50 [Short Paper] Sketch-based CT image generation of lung cancers using Pix2pix -- An attempt to improve representation by adopting Style Blocks -- Ryo Toda, Atsushi Teramoto (FHU), Masakazu Tsujimoto (FHUH), Hiroshi Toyama, Masashi Kondo, Kazuyoshi Imaizumi, Kuniaki Saito (FHU), Hiroshi Fujita (Gifu Univ.)  MICT2021-42 MI2021-40 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Generative adversarial networks (GAN) have been used to overcome the lack of data in medical images. However, such applications only rarely focus on controlling the variation and shape of the generated lesion images. In this study, we introduce Pix2pix, a derivative of GAN, to generate images with precisely controlled lesion shapes by sketching. In addition, to capture the features difficult to be represented by sketching, such as noise specific to CT images, the model adopting the style-based architecture proposed in StyleGAN is used. As a preliminary study, the feasibility of our method was verified by using CT images of lung cancer, which are relatively easy to obtain. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Generative adversarial networks / Computed tomography / Lung cancer / Image synthesis / Style / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 231, MI2021-40, pp. 66-67, Nov. 2021. | |
| Paper # | MI2021-40 | |
| Date of Issue | 2021-10-29 (MICT, 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 | MICT2021-42 MI2021-40 |
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| Conference Information | |
| Committee | MI MICT |
| Conference Date | 2021-11-05 - 2021-11-05 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical imaging technology, healthcare and medical information communication technology |
| Paper Information | |
| Registration To | MI |
| Conference Code | 2021-11-MI-MICT |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Sketch-based CT image generation of lung cancers using Pix2pix |
| Sub Title (in English) | An attempt to improve representation by adopting Style Blocks |
| Keyword(1) | Generative adversarial networks |
| Keyword(2) | Computed tomography |
| Keyword(3) | Lung cancer |
| Keyword(4) | Image synthesis |
| Keyword(5) | Style |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Ryo Toda |
| 1st Author's Affiliation | Fujita Health University (FHU) |
| 2nd Author's Name | Atsushi Teramoto |
| 2nd Author's Affiliation | Fujita Health University (FHU) |
| 3rd Author's Name | Masakazu Tsujimoto |
| 3rd Author's Affiliation | Fujita Health University Hospital (FHUH) |
| 4th Author's Name | Hiroshi Toyama |
| 4th Author's Affiliation | Fujita Health University (FHU) |
| 5th Author's Name | Masashi Kondo |
| 5th Author's Affiliation | Fujita Health University (FHU) |
| 6th Author's Name | Kazuyoshi Imaizumi |
| 6th Author's Affiliation | Fujita Health University (FHU) |
| 7th Author's Name | Kuniaki Saito |
| 7th Author's Affiliation | Fujita Health University (FHU) |
| 8th Author's Name | Hiroshi Fujita |
| 8th Author's Affiliation | Gifu University (Gifu Univ.) |
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| Speaker | Author-1 |
| Date Time | 2021-11-05 15:50:00 |
| Presentation Time | 20 minutes |
| Registration for | MI |
| Paper # | MICT2021-42, MI2021-40 |
| Volume (vol) | vol.121 |
| Number (no) | no.230(MICT), no.231(MI) |
| Page | pp.66-67 |
| #Pages | 2 |
| Date of Issue | 2021-10-29 (MICT, MI) |
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