output
20172022
most cited3D Reconstruction of Coronary Arteries and Atherosclerotic Plaques based on Computed Tomography Angiography Images

48 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

6 papers

physics.flu-dyn2022★ 33 cited

High fidelity fluid-structure interaction by radial basis functions mesh adaption of moving walls: a workflow applied to an aortic valve

Leonardo Geronzi, Emanuele Gasparotti, Katia Capellini +6

Fluid-Structure Interaction (FSI) can be investigated by means of non-linear Finite Element Models (FEM), suitable to capture large deflections of structural parts interacting with…

physics.ins-det2020★ 17 cited

Quantitative Imaging and Automated Fuel Pin Identification for Passive Gamma Emission Tomography

Ming Fang, Yoann Altmann, Daniele Della Latta +2

Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography system is a nov…

eess.IV2019★ 48 cited

3D Reconstruction of Coronary Arteries and Atherosclerotic Plaques based on Computed Tomography Angiography Images

Vassiliki I. Kigka, George Rigas, Antonis Sakellarios +10

The purpose of this study is to present a new semi-automated methodology for three-dimensional (3D) reconstruction of coronary arteries and their plaque morphology using Computed T…

cs.CV2018

Training of a Skull-Stripping Neural Network with efficient data augmentation

Gabriele Valvano, Nicola Martini, Andrea Leo +4

Skull-stripping methods aim to remove the non-brain tissue from acquisition of brain scans in magnetic resonance (MR) imaging. Although several methods sharing this common purpose…

cs.CV2018

Convolutional Neural Networks for the segmentation of microcalcification in Mammography Imaging

Gabriele Valvano, Gianmarco Santini, Nicola Martini +4

Cluster of microcalcifications can be an early sign of breast cancer. In this paper we propose a novel approach based on convolutional neural networks for the detection and segment…

cs.CV2017★ 22 cited

An automatic deep learning approach for coronary artery calcium segmentation

G. Santini, D. Della Latta, N. Martini +6

Coronary artery calcium (CAC) is a significant marker of atherosclerosis and cardiovascular events. In this work we present a system for the automatic quantification of calcium sco…