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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

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6 papers · 1 filter

cs.CV2018

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

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

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

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…

cs.CV20179 cited

Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images

Jelmer M. Wolterink, Tim Leiner, Max A. Viergever +1

Segmentation of the heart in cardiac cine MR is clinically used to quantify cardiac function. We propose a fully automatic method for segmentation and disease classification using…