Integrating partial volume modeling into automatic coronary lumen segmentation from CCTA raises flow-simulation specificity from 0.6 to 0.68 and AUC from 0.76 to 0.8 for detecting lesions with invasive FFR below 0.8.
Quantitative analysis of the CAD from CCTA required both automatic extraction of the coronaries’ centerlines30–34 and automatic segmentation of the coronaries lumen
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Improving CCTA based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation
Integrating partial volume modeling into automatic coronary lumen segmentation from CCTA raises flow-simulation specificity from 0.6 to 0.68 and AUC from 0.76 to 0.8 for detecting lesions with invasive FFR below 0.8.