activity
20192022
most citedCoronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics

21 citations · 24 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV20222 cited

CAD-RADS Scoring using Deep Learning and Task-Specific Centerline Labeling

Felix Denzinger, Michael Wels, Oliver Taubmann +8

With coronary artery disease (CAD) persisting to be one of the leading causes of death worldwide, interest in supporting physicians with algorithms to speed up and improve diagnosi…

cs.CV2021

Coronary Plaque Analysis for CT Angiography Clinical Research

Felix Denzinger, Michael Wels, Christian Hopfgartner +4

The analysis of plaque deposits in the coronary vasculature is an important topic in current clinical research. From a technical side mostly new algorithms for different sub tasks…

eess.IV2020

Automatic CAD-RADS Scoring Using Deep Learning

Felix Denzinger, Michael Wels, Katharina Breininger +7

Coronary CT angiography (CCTA) has established its role as a non-invasive modality for the diagnosis of coronary artery disease (CAD). The CAD-Reporting and Data System (CAD-RADS)…

eess.IV20191 cited

Deep Learning Algorithms for Coronary Artery Plaque Characterisation from CCTA Scans

Felix Denzinger, Michael Wels, Katharina Breininger +5

Analysing coronary artery plaque segments with respect to their functional significance and therefore their influence to patient management in a non-invasive setup is an important…

eess.IV201921 cited

Coronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics

Felix Denzinger, Michael Wels, Nishant Ravikumar +6

Assessing coronary artery plaque segments in coronary CT angiography scans is an important task to improve patient management and clinical outcomes, as it can help to decide whethe…