Automatic Coronary Artery Plaque Quantification and CAD-RADS Prediction using Mesh Priors

no code implementations • 17 Oct 2023 • Rudolf L. M. van Herten, Nils Hampe, Richard A. P. Takx, Klaas Jan Franssen, Yining Wang, Dominika Suchá, José P. Henriques, Tim Leiner, R. Nils Planken, Ivana Išgum

This requires analysis of the coronary lumen and plaque.

Deep Learning from Dual-Energy Information for Whole-Heart Segmentation in Dual-Energy and Single-Energy Non-Contrast-Enhanced Cardiac CT

no code implementations • 10 Aug 2020 • Steffen Bruns, Jelmer M. Wolterink, Richard A. P. Takx, Robbert W. van Hamersvelt, Dominika Suchá, Max A. Viergever, Tim Leiner, Ivana Išgum

Deep learning-based whole-heart segmentation in coronary CT angiography (CCTA) allows the extraction of quantitative imaging measures for cardiovascular risk prediction.

Heart Segmentation Segmentation

Deep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images

no code implementations • 10 Jul 2020 • Julia M. H. Noothout, Bob D. de Vos, Jelmer M. Wolterink, Elbrich M. Postma, Paul A. M. Smeets, Richard A. P. Takx, Tim Leiner, Max A. Viergever, Ivana Išgum

Global landmark locations are obtained by averaging the predicted displacement vectors, where the contribution of each displacement vector is weighted by the posterior classification probability of the patch that it is pointing from.

Classification General Classification +1