5 papers
Uncertainty-Guided Conservative Propagation for Structured Inference in Vessel Segmentation
Huan Huang, Michele Esposito, Chen Zhao
Accurate vessel segmentation is essential for medical image analysis, yet remains challenging due to complex vascular patterns and imaging ambiguity. Most deep models rely on singl…
Imaging-Derived Coronary Fractional Flow Reserve: Advances in Physics-Based, Machine Learning, and Physics-Informed Methods
Tanxin Zhu, Emran Hossen, Chen Zhao +4
Purpose of Review Imaging derived fractional flow reserve (FFR) is rapidly evolving beyond conventional computational fluid dynamics (CFD) based pipelines toward machine learning (…
Anatomy Guided Coronary Artery Segmentation from CCTA Using Spatial Frequency Joint Modeling
Huan Huang, Michele Esposito, Chen Zhao
Accurate coronary artery segmentation from coronary computed tomography angiography is essential for quantitative coronary analysis and clinical decision support. Nevertheless, rel…
Blood Pressure Prediction for Coronary Artery Disease Diagnosis using Coronary Computed Tomography Angiography
Rene Lisasi, Michele Esposito, Chen Zhao
Computational fluid dynamics (CFD) based simulation of coronary blood flow provides valuable hemodynamic markers, such as pressure gradients, for diagnosing coronary artery disease…
A review on machine learning for arterial extraction and quantitative assessment on invasive coronary angiograms
Pukar Baral, Chen Zhao, Michele Esposito +1
Purpose of Review Recently, machine learning has developed rapidly in the field of medicine, playing an important role in disease diagnosis. Our aim of this paper is to provide an…