20 citations · 22 across the 8 of their papers we have counts for
8 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…
MitraClip Device Automated Localization in 3D Transesophageal Echocardiography via Deep Learning
Riccardo Munafò, Simone Saitta, Luca Vicentini +7
The MitraClip is the most widely percutaneous treatment for mitral regurgitation, typically performed under the real-time guidance of 3D transesophagel echocardiography (TEE). Howe…
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…
Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI
Simone Saitta, Marcello Carioni, Subhadip Mukherjee +2
4D flow MRI is a non-invasive imaging method that can measure blood flow velocities over time. However, the velocity fields detected by this technique have limitations due to low r…
A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning
Simone Saitta, Francesco Sturla, Riccardo Gorla +4
Accurate planning of transcatheter aortic implantation (TAVI) is important to minimize complications, and it requires anatomic evaluation of the aortic root (AR), commonly done thr…
A Deep Learning-Based Fully Automated Pipeline for Regurgitant Mitral Valve Anatomy Analysis From 3D Echocardiography
Riccardo Munafò, Simone Saitta, Giacomo Ingallina +5
Three-dimensional transesophageal echocardiography (3DTEE) is the recommended imaging technique for the assessment of mitral valve (MV) morphology and lesions in case of mitral reg…
Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta
Simone Saitta, Ludovica Maga, Chloe Armour +8
Numerical simulations of blood flow are a valuable tool to investigate the pathophysiology of ascending thoracic aortic aneurysms (ATAA). To accurately reproduce hemodynamics, comp…