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Featured Co-authors

Bram van Ginneken
49 publications
Jelmer M. Wolterink
34 publications
Konstantinos Kamnitsas
30 publications
Max A. Viergever
26 publications
Tim Leiner
16 publications
Marius Staring
16 publications
Hugo J. Kuijf
15 publications
Bob D. de Vos
14 publications
Mohsen Ghafoorian
12 publications
Nikolas Lessmann
12 publications
Bas H. M. van der Velden
9 publications

research

∙ 08/09/2023

Deep Learning-Based Prediction of Fractional Flow Reserve along the Coronary Artery

Functionally significant coronary artery disease (CAD) is caused by plaq...

0 Nils Hampe, et al. ∙

research

∙ 05/24/2022

Generative Models for Reproducible Coronary Calcium Scoring

Purpose: Coronary artery calcium (CAC) score, i.e. the amount of CAC qua...

0 Sanne G. M. van Velzen, et al. ∙

research

∙ 02/18/2022

Autoencoding Low-Resolution MRI for Semantically Smooth Interpolation of Anisotropic MRI

High-resolution medical images are beneficial for analysis but their acq...

5 Jörg Sander, et al. ∙

research

∙ 11/13/2020

Automatic segmentation with detection of local segmentation failures in cardiac MRI

Segmentation of cardiac anatomical structures in cardiac magnetic resona...

1 Jörg Sander, et al. ∙

research

∙ 10/25/2020

Unsupervised Super-Resolution: Creating High-Resolution Medical Images from Low-Resolution Anisotropic Examples

Although high resolution isotropic 3D medical images are desired in clin...

0 Jörg Sander, et al. ∙

research

∙ 10/01/2020

Deep Group-wise Variational Diffeomorphic Image Registration

Deep neural networks are increasingly used for pair-wise image registrat...

9 Tycho F. A. van der Ouderaa, et al. ∙

research

∙ 08/10/2020

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

Deep learning-based whole-heart segmentation in coronary CT angiography ...

0 Steffen Bruns, et al. ∙

research

∙ 07/10/2020

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

In this study, we propose a fast and accurate method to automatically lo...

49 Julia M. H. Noothout, et al. ∙

research

∙ 11/12/2019

Automatic Online Quality Control of Synthetic CTs

Accurate MR-to-CT synthesis is a requirement for MR-only workflows in ra...

29 Louis D. van Harten, et al. ∙

research

∙ 11/12/2019

Exploiting Clinically Available Delineations for CNN-based Segmentation in Radiotherapy Treatment Planning

Convolutional neural networks (CNNs) have been widely and successfully u...

31 Louis D. van Harten, et al. ∙

research

∙ 11/10/2019

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

Treatment of patients with obstructive coronary artery disease is guided...

24 Majd Zreik, et al. ∙

research

∙ 08/27/2019

3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations

We propose a supervised nonrigid image registration method, trained usin...

3 Hessam Sokooti, et al. ∙

research

∙ 08/14/2019

Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography

Detection of coronary artery stenosis in coronary CT angiography (CCTA) ...

4 Jelmer M. Wolterink, et al. ∙

research

∙ 06/28/2019

Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy

Joint image registration and segmentation has long been an active area o...

6 Mohamed S. Elmahdy, et al. ∙

research

∙ 06/11/2019

Deep learning analysis of cardiac CT angiography for detection of coronary arteries with functionally significant stenosis

In patients with obstructive coronary artery disease, the functional sig...

8 Majd Zreik, et al. ∙

research

∙ 02/12/2019

Direct Automatic Coronary Calcium Scoring in Cardiac and Chest CT

Cardiovascular disease (CVD) is the global leading cause of death. A str...

38 Bob D. de Vos, et al. ∙

research

∙ 11/22/2018

Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing

Response of breast cancer to neoadjuvant chemotherapy (NAC) can be monit...

10 Bas H. M. van der Velden, et al. ∙

research

∙ 10/24/2018

Generative adversarial networks and adversarial methods in biomedical image analysis

Generative adversarial networks (GANs) and other adversarial methods are...

4 Jelmer M. Wolterink, et al. ∙

research

∙ 10/09/2018

Automatic Segmentation of Thoracic Aorta Segments in Low-Dose Chest CT

Morphological analysis and identification of pathologies in the aorta ar...

0 Julia M. H. Noothout, et al. ∙

research

∙ 10/07/2018

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

Coronary artery centerline extraction in cardiac CT angiography (CCTA) i...

2 Jelmer M. Wolterink, et al. ∙

research

∙ 10/04/2018

Direct Prediction of Cardiovascular Mortality from Low-dose Chest CT using Deep Learning

Cardiovascular disease (CVD) is a leading cause of death in the lung can...

6 Sanne G. M. van Velzen, et al. ∙

research

∙ 09/27/2018

Improving Myocardium Segmentation in Cardiac CT Angiography using Spectral Information

Accurate segmentation of the left ventricle myocardium in cardiac CT ang...

0 Steffen Bruns, et al. ∙

research

∙ 09/27/2018

Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI

Current state-of-the-art deep learning segmentation methods have not yet...

4 Jörg Sander, et al. ∙

research

∙ 09/17/2018

A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration

Image registration, the process of aligning two or more images, is the c...

0 Bob D. de Vos, et al. ∙

research

∙ 04/13/2018

CNN-based Landmark Detection in Cardiac CTA Scans

Fast and accurate anatomical landmark detection can benefit many medical...

0 Julia M. H. Noothout, et al. ∙

research

∙ 04/12/2018

Iterative fully convolutional neural networks for automatic vertebra segmentation

Precise segmentation of the vertebrae is often required for automatic de...

0 Nikolas Lessmann, et al. ∙

research

∙ 04/12/2018

Blood Vessel Geometry Synthesis using Generative Adversarial Networks

Computationally synthesized blood vessels can be used for training and e...

0 Jelmer M. Wolterink, et al. ∙

research

∙ 04/12/2018

Automatic Detection and Characterization of Coronary Artery Plaque and Stenosis using a Recurrent Convolutional Neural Network in Coronary CT Angiography

Different types of atherosclerotic plaque and varying grades of stenosis...

0 Majd Zreik, et al. ∙

research

∙ 12/08/2017

Direct and Real-Time Cardiovascular Risk Prediction

Coronary artery calcium (CAC) burden quantified in low-dose chest CT is ...

0 Bob D. de Vos, et al. ∙

research

∙ 11/24/2017

Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis

In patients with coronary artery stenoses of intermediate severity, the ...

0 Majd Zreik, et al. ∙

research

∙ 11/01/2017

Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions

Heavy smokers undergoing screening with low-dose chest CT are affected b...

0 Nikolas Lessmann, et al. ∙

research

∙ 08/03/2017

Deep MR to CT Synthesis using Unpaired Data

MR-only radiotherapy treatment planning requires accurate MR-to-CT synth...

0 Jelmer M. Wolterink, et al. ∙

research

∙ 08/03/2017

Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images

Segmentation of the heart in cardiac cine MR is clinically used to quant...

0 Jelmer M. Wolterink, et al. ∙

research

∙ 04/11/2017

Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities

Automatic segmentation of medical images is an important task for many c...

0 Pim Moeskops, et al. ∙

research

∙ 04/11/2017

Automatic segmentation of MR brain images with a convolutional neural network

Automatic segmentation in MR brain images is important for quantitative ...

0 Pim Moeskops, et al. ∙

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