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CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: a clinically-inspired deep learning pipeline. (arXiv:2304.07277v1 [eess.IV])
cs.LG updates on arXiv.org arxiv.org
The standard non-invasive imaging technique used to assess the severity and
extent of Coronary Artery Disease (CAD) is Coronary Computed Tomography
Angiography (CCTA). However, manual grading of each patient's CCTA according to
the CAD-Reporting and Data System (CAD-RADS) scoring is time-consuming and
operator-dependent, especially in borderline cases. This work proposes a fully
automated, and visually explainable, deep learning pipeline to be used as a
decision support system for the CAD screening procedure. The pipeline performs
two classification tasks: firstly, identifying …
arxiv cad cases classification data decision decision support deep learning disease imaging patient patients pipeline reporting scoring screening standard support transformer vision work