Comparative analysis between convolutional long short-term memory networks and vision transformers for coronary calcium scoring in non-contrast CT

Aakash D. Shanbhag; Konrad Pieszko; Robert J.H. Miller; Aditya Killekar; Waechter Parker; Heidi Gransar; Michelle Williams; Daniel S. Berman; Damini Dey; Piotr J. Slomka

doi:10.1117/12.2655397

3 April 2023 Comparative analysis between convolutional long short-term memory networks and vision transformers for coronary calcium scoring in non-contrast CT

Aakash D. Shanbhag, Konrad Pieszko, Robert J.H. Miller, Aditya Killekar, Waechter Parker, Heidi Gransar, Michelle Williams, Daniel S. Berman, Damini Dey, Piotr J. Slomka

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Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124640D (2023) https://doi.org/10.1117/12.2655397
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

Coronary artery calcium (CAC) scores are a well-established marker of the extent of coronary atherosclerosis. We aimed to compare state-of-the-art vision transformer for medical image segmentation with convolutional long short-term memory (convLSTM) networks for automatic CAC quantification with external validation.

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Aakash D. Shanbhag, Konrad Pieszko, Robert J.H. Miller, Aditya Killekar, Waechter Parker, Heidi Gransar, Michelle Williams, Daniel S. Berman, Damini Dey, and Piotr J. Slomka "Comparative analysis between convolutional long short-term memory networks and vision transformers for coronary calcium scoring in non-contrast CT", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124640D (3 April 2023); https://doi.org/10.1117/12.2655397

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