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Jelmer M. Wolterink

Researcher at University of Twente

Publications -  101
Citations -  5394

Jelmer M. Wolterink is an academic researcher from University of Twente. The author has contributed to research in topics: Deep learning & Computer science. The author has an hindex of 23, co-authored 82 publications receiving 3312 citations. Previous affiliations of Jelmer M. Wolterink include University of Amsterdam & Utrecht University.

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Journal ArticleDOI

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

TL;DR: How far state-of-the-art deep learning methods can go at assessing CMRI, i.e., segmenting the myocardium and the two ventricles as well as classifying pathologies is measured, to open the door to highly accurate and fully automatic analysis of cardiac CMRI.
Journal ArticleDOI

Generative Adversarial Networks for Noise Reduction in Low-Dose CT

TL;DR: Noise reduction improved quantification of low-density calcified inserts in phantom CT images and allowed coronary calcium scoring in low-dose patient CT images with high noise levels.
Book ChapterDOI

Deep MR to CT synthesis using unpaired data

TL;DR: This work proposes to train a generative adversarial network (GAN) with unpaired MR and CT images to synthesize CT images that closely approximate reference CT images, and was able to outperform a GAN model trained with paired MR andCT images.
Book ChapterDOI

Deep learning for multi-task medical image segmentation in multiple modalities

TL;DR: In this article, a single convolutional neural network (CNN) is trained to perform different segmentation tasks for different medical images, such as image segmentation, segmentation of anatomical structures, and image classification.
Journal ArticleDOI

Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks.

TL;DR: CAC can be accurately automatically identified and quantified in CCTA using the proposed pattern recognition method, which might obviate the need to acquire a dedicated CSCT scan for CAC scoring, and thus reduce the CT radiation dose received by patients.