7 citations · 16 across the 7 of their papers we have counts for
7 papers
Pericoronary adipose tissue attenuation as a predictor of functional severity of coronary stenosis
Marta Pillitteri, Guido Nannini, Simone Saitta +5
Objective: This study aims to evaluate the functional significance of coronary stenosis by analyzing low-level radiomic features of the pericoronary adipose tissue (PCAT) surroundi…
Learning Hemodynamic Scalar Fields on Coronary Artery Meshes: A Benchmark of Geometric Deep Learning Models
Guido Nannini, Julian Suk, Patryk Rygiel +7
Coronary artery disease, caused by the narrowing of coronary vessels due to atherosclerosis, is the leading cause of death worldwide. The diagnostic gold standard, fractional flow…
Deep vectorised operators for pulsatile hemodynamics estimation in coronary arteries from a steady-state prior
Julian Suk, Guido Nannini, Patryk Rygiel +4
Cardiovascular hemodynamic fields provide valuable medical decision markers for coronary artery disease. Computational fluid dynamics (CFD) is the gold standard for accurate, non-i…
An automated and time efficient framework for simulation of coronary blood flow under steady and pulsatile conditions
Guido Nannini, Simone Saitta, Luca Mariani +5
Fractional flow reserve (FFR) is the gold standard for diagnosing coronary artery disease (CAD). FFRCT uses computational fluid dynamics (CFD) to evaluate FFR non-invasively by sim…
Two new calibration techniques of lumped-parameter mathematical models for the cardiovascular system
Andrea Tonini, Francesco Regazzoni, Matteo Salvador +7
Cardiocirculatory mathematical models serve as valuable tools for investigating physiological and pathological conditions of the circulatory system. To investigate the clinical con…
CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: a clinically-inspired deep learning pipeline
Alessia Gerbasi, Arianna Dagliati, Giuseppe Albi +7
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, man…
Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional LSTM networks
Kajetan Grodecki, Aditya Killekar, Andrew Lin +22
Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease (COVID-19) patients, but are not part of t…