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20172022
most citedDeep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities

333 citations · 1.6k across the 20 of their papers we have counts for

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Showing 2018Show all

5 papers · 1 filter

cs.CV2018★ 211 cited

Coronary Artery Centerline Extraction in Cardiac CT Angiography Using a CNN-Based Orientation Classifier

Jelmer M. Wolterink, Robbert W. van Hamersvelt, Max A. Viergever +2

Coronary artery centerline extraction in cardiac CT angiography (CCTA) images is a prerequisite for evaluation of stenoses and atherosclerotic plaque. We propose an algorithm that…

cs.CV2018

Improving Myocardium Segmentation in Cardiac CT Angiography using Spectral Information

Steffen Bruns, Jelmer M. Wolterink, Robbert W. van Hamersvelt +3

Accurate segmentation of the left ventricle myocardium in cardiac CT angiography (CCTA) is essential for e.g. the assessment of myocardial perfusion. Automatic deep learning method…

cs.CV2018★ 25 cited

CNN-based Landmark Detection in Cardiac CTA Scans

Julia M. H. Noothout, Bob D. de Vos, Jelmer M. Wolterink +2

Fast and accurate anatomical landmark detection can benefit many medical image analysis methods. Here, we propose a method to automatically detect anatomical landmarks in medical i…

cs.CV2018★ 12 cited

Blood Vessel Geometry Synthesis using Generative Adversarial Networks

Jelmer M. Wolterink, Tim Leiner, Ivana Isgum

Computationally synthesized blood vessels can be used for training and evaluation of medical image analysis applications. We propose a deep generative model to synthesize blood ves…

cs.CV2018★ 281 cited

A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography

Majd Zreik, Robbert W. van Hamersvelt, Jelmer M. Wolterink +3

Various types of atherosclerotic plaque and varying grades of stenosis could lead to different management of patients with coronary artery disease. Therefore, it is crucial to dete…