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Paper Abstract and Keywords
Presentation 2023-03-27 09:00
Medical Image Segmentation with Inverse Heat Dissipation Model
Yu Kashihara, Takashi Matsubara (Osaka Univ.) CCS2022-82
Abstract (in Japanese) (See Japanese page) 
(in English) The diffusion model is a generative model based on stochastic transitions and has been successfully used to generate
and edit images. Its superior sampling ability has the potential to enable more detailed segmentation of images. This study
presents a novel approach to segmentation tasks using the inverse heat dissipation model, one of the diffusion-based models.
Our proposed method involves generating a mask that gradually shrinks to fit the shape of the desired segmentation region.
The proposed method uses the inverse heat dissipation model to generate a mask that fits the details from the coarse masks of
other models. The segmentation model based on the diffusion model has the problem of unstable mask shape for each trial.
We addressed this issue by using masks from other models as the initial mask to assist in stochastic generation trajectories. We
evaluated the proposed method on various medical datasets to study its effectiveness and generality. The results show that the
proposed method outperforms existing methods and provides a more detailed segmentation.
Keyword (in Japanese) (See Japanese page) 
(in English) diffusion-based models / inverse heat dissipation model / medical image segmentation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 453, CCS2022-82, pp. 107-112, March 2023.
Paper # CCS2022-82 
Date of Issue 2023-03-19 (CCS) 
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 CCS2022-82

Conference Information
Committee CCS  
Conference Date 2023-03-26 - 2023-03-27 
Place (in Japanese) (See Japanese page) 
Place (in English) RUSUTSU RESORT 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CCS 
Conference Code 2023-03-CCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Medical Image Segmentation with Inverse Heat Dissipation Model 
Sub Title (in English)  
Keyword(1) diffusion-based models  
Keyword(2) inverse heat dissipation model  
Keyword(3) medical image segmentation  
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1st Author's Name Yu Kashihara  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Takashi Matsubara  
2nd Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2023-03-27 09:00:00 
Presentation Time 20 minutes 
Registration for CCS 
Paper # CCS2022-82 
Volume (vol) vol.122 
Number (no) no.453 
Page pp.107-112 
#Pages
Date of Issue 2023-03-19 (CCS) 


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