Coronary calcium detection using 3D attention identical dual deep network based on weakly supervised learning

Yuankai Huo; James G. Terry; Jiachen Wang; Vishwesh Nath; Camilo Bermudez; Shunxing Bao; Prasanna Parvathaneni; J. Jeffery Carr; Bennett A. Landman

doi:10.1117/12.2512541

15 March 2019 Coronary calcium detection using 3D attention identical dual deep network based on weakly supervised learning

Yuankai Huo, James G. Terry, Jiachen Wang, Vishwesh Nath, Camilo Bermudez, Shunxing Bao, Prasanna Parvathaneni, J. Jeffery Carr, Bennett A. Landman

Author Affiliations +

Proceedings Volume 10949, Medical Imaging 2019: Image Processing; 1094917 (2019) https://doi.org/10.1117/12.2512541
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

Coronary artery calcium (CAC) is biomarker of advanced subclinical coronary artery disease and predicts myocardial infarction and death prior to age 60 years. The slice-wise manual delineation has been regarded as the gold standard of coronary calcium detection. However, manual efforts are time and resource consuming and even impracticable to be applied on large-scale cohorts. In this paper, we propose the attention identical dual network (AID-Net) to perform CAC detection using scan-rescan longitudinal non-contrast CT scans with weakly supervised attention by only using per scan level labels. To leverage the performance, 3D attention mechanisms were integrated into the AID-Net to provide complementary information for classification tasks. Moreover, the 3D Gradient-weighted Class Activation Mapping (Grad-CAM) was also proposed at the testing stage to interpret the behaviors of the deep neural network. 5075 non-contrast chest CT scans were used as training, validation and testing datasets. Baseline performance was assessed on the same cohort. From the results, the proposed AID-Net achieved the superior performance on classification accuracy (0.9272) and AUC (0.9627).

Conference Presentation

Citation Download Citation

Yuankai Huo, James G. Terry, Jiachen Wang, Vishwesh Nath, Camilo Bermudez, Shunxing Bao, Prasanna Parvathaneni, J. Jeffery Carr, and Bennett A. Landman "Coronary calcium detection using 3D attention identical dual deep network based on weakly supervised learning", Proc. SPIE 10949, Medical Imaging 2019: Image Processing, 1094917 (15 March 2019); https://doi.org/10.1117/12.2512541

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

Includes PDF, HTML & Video, when available