Improved coronary artery calcium (CAC) detection in conventional CT with deep-learning image de-blurring

Christian Wülker; Niels R. van der Werf; Nikolas D. Schnellbächer; Marcel J. W. Greuter; Michael Grass

doi:10.1117/12.3006693

1 April 2024 Improved coronary artery calcium (CAC) detection in conventional CT with deep-learning image de-blurring

Christian Wülker, Niels R. van der Werf, Nikolas D. Schnellbächer, Marcel J. W. Greuter, Michael Grass

Proceedings Volume 12925, Medical Imaging 2024: Physics of Medical Imaging; 129252B (2024) https://doi.org/10.1117/12.3006693
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

We investigated the impact of a CNN-based deep-learning (DL) image de-blurring algorithm on coronary artery calcium (CAC) detection performance in conventional CT imaging. Our approach comprises first de-noising the image with a state-of-the-art CNN-based image de-noising algorithm. With improved SNR, it is then possible to sharpen the image with a CNN-based image de-blurring algorithm. We train such networks using natural images, i.e., a large set of diverse photographs. The de-noising strength in the final image can be adjusted by blending back the estimated noise from the first step to the desired degree. To assess the impact of the de-blurring algorithm, we scanned an anthropomorphic phantom containing 100 small calcifications on a CT system using a CAC scoring protocol. Data were acquired at clinical and high dose, and subsequently reconstructed with and without the DL de-blurring algorithm, using 25% of the maximum de-noising strength. For each small CAC, detectability was defined as the ability to calculate an Agatston score (at least 3 adjacent voxels exceeding 130 HU). For the high dose scans, CAC detectability increased from 39% for the standard reconstruction to 49% with de-blurring. The same 39% CAC detectability at high dose without de-blurring was obtained with routine dose with de-blurring. In this work, we also show some visual impressions of applying our DL de-blurring method to clinical cardiac data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Christian Wülker, Niels R. van der Werf, Nikolas D. Schnellbächer, Marcel J. W. Greuter, and Michael Grass "Improved coronary artery calcium (CAC) detection in conventional CT with deep-learning image de-blurring", Proc. SPIE 12925, Medical Imaging 2024: Physics of Medical Imaging, 129252B (1 April 2024); https://doi.org/10.1117/12.3006693

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