activity
20172020
most citedDeep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images

122 citations · 184 across the 4 of their papers we have counts for

collaborators

12 papers

eess.IV202053 cited

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

Steffen Bruns, Jelmer M. Wolterink, Richard A. P. Takx +5

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

eess.IV2020122 cited

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

Julia M. H. Noothout, Bob D. de Vos, Jelmer M. Wolterink +6

In this study, we propose a fast and accurate method to automatically localize anatomical landmarks in medical images. We employ a global-to-local localization approach using fully…

eess.IV2019

Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis

Majd Zreik, Tim Leiner, Nadieh Khalili +5

Treatment of patients with obstructive coronary artery disease is guided by the functional significance of a coronary artery stenosis. Fractional flow reserve (FFR), measured durin…

eess.IV2019

CNN-Based Segmentation of the Cardiac Chambers and Great Vessels in Non-Contrast-Enhanced Cardiac CT

Steffen Bruns, Jelmer M. Wolterink, Robbert W. van Hamersvelt +2

Quantification of cardiac structures in non-contrast CT (NCCT) could improve cardiovascular risk stratification. However, setting a manual reference to train a fully convolutional…

eess.IV2019

Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography

Jelmer M. Wolterink, Tim Leiner, Ivana Išgum

Detection of coronary artery stenosis in coronary CT angiography (CCTA) requires highly personalized surface meshes enclosing the coronary lumen. In this work, we propose to use gr…

eess.IV2019

Deep learning analysis of coronary arteries in cardiac CT angiography for detection of patients requiring invasive coronary angiography

Majd Zreik, Robbert W. van Hamersvelt, Nadieh Khalili +5

In patients with obstructive coronary artery disease, the functional significance of a coronary artery stenosis needs to be determined to guide treatment. This is typically establi…