CNN-Based Segmentation of the Cardiac Chambers and Great Vessels in Non-Contrast-Enhanced Cardiac CT

Steffen Bruns, Jelmer M. Wolterink, Robbert W. van Hamersvelt, Tim Leiner, Ivana Išgum

Keywords: Cardiac segmentation, convolutional neural network, non-contrast-enhanced CT, dual-energy CT

Abstract: Quantification of cardiac structures in non-contrast CT (NCCT) could improve cardiovascular risk stratification. However, setting a manual reference to train a fully convolutional network (FCN) for automatic segmentation of NCCT images is hardly feasible, and an FCN trained on coronary CT angiography (CCTA) images would not generalize to NCCT. Therefore, we propose to train an FCN with virtual non-contrast (VNC) images from a dual-layer detector CT scanner and a reference standard obtained on perfectly aligned CCTA images.

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