Transformation-consistent semi-supervised learning for prostate CT radiotherapy

Yichao Li; Mohamed S. Elmahdy; Michael S. Lew; Marius Staring

doi:10.1117/12.2604968

4 April 2022 Transformation-consistent semi-supervised learning for prostate CT radiotherapy

Yichao Li, Mohamed S. Elmahdy, Michael S. Lew, Marius Staring

Author Affiliations +

Proceedings Volume 12033, Medical Imaging 2022: Computer-Aided Diagnosis; 120333O (2022) https://doi.org/10.1117/12.2604968
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

Deep supervised models often require a large amount of labelled data, which is difficult to obtain in the medical domain. Therefore, semi-supervised learning (SSL) has been an active area of research due to its promise to minimize training costs by leveraging unlabelled data. Previous research have shown that SSL is especially effective in low labelled data regimes, we show that outperformance can be extended to high data regimes by applying Stochastic Weight Averaging (SWA), which incurs zero additional training cost. Our model was trained on a prostate CT dataset and achieved improvements of 0.12 mm, 0.14 mm, 0.32 mm, and 0.14 mm for the prostate, seminal vesicles, rectum, and bladder respectively, in terms of median test set mean surface distance (MSD) compared to the supervised baseline in our high data regime.

Conference Presentation

Citation Download Citation

Yichao Li, Mohamed S. Elmahdy, Michael S. Lew, and Marius Staring "Transformation-consistent semi-supervised learning for prostate CT radiotherapy", Proc. SPIE 12033, Medical Imaging 2022: Computer-Aided Diagnosis, 120333O (4 April 2022); https://doi.org/10.1117/12.2604968

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