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.
Accurate Quantification of Small-Diameter Tubular Structures in Isotropic CT Volume Data Based on Multiscale Line Filter Responses
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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.