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.
Diagnostic performance of non-invasive fractional flow reserve derived from coronary CT angiography in suspected coronary artery disease: The NXT trial
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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.