Strict source-free domain adaptation with simple assumptions for cardiac segmentation

Hirohisa Oda; Mayu Wakamori; Toshiaki Akita

doi:10.1117/12.3057249

5 February 2025 Strict source-free domain adaptation with simple assumptions for cardiac segmentation

Hirohisa Oda, Mayu Wakamori, Toshiaki Akita

Author Affiliations +

Proceedings Volume 13510, International Workshop on Advanced Imaging Technology (IWAIT) 2025; 1351007 (2025) https://doi.org/10.1117/12.3057249
Event: International Workshop on Advanced Imaging Technology (IWAIT) 2025, 2025, Douliu City, Taiwan

Abstract

This paper proposes a method of source-free domain adaptation (SFDA) with a novel early stopping criterion for cardiac segmentation between CT and MRI. This approach enables stable segmentation when adapting a model trained on one modality to perform well on the other, while eliminating the need for ground-truth labels of the target domain. The proposed criterion evaluates segmentation results by aligning them with expected cardiac features, such as the heart’s near-spherical shape and distinct regions. This enables the model to stop training at an optimal point for accurate segmentation. Experiments using 20 CT and MRI volumes showed that our method achieved results comparable to partly using target domain’s ground-truth.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hirohisa Oda, Mayu Wakamori, and Toshiaki Akita "Strict source-free domain adaptation with simple assumptions for cardiac segmentation", Proc. SPIE 13510, International Workshop on Advanced Imaging Technology (IWAIT) 2025, 1351007 (5 February 2025); https://doi.org/10.1117/12.3057249

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE