843 citations · 1.5k across the 13 of their papers we have counts for
14 papers
Autoencoding Low-Resolution MRI for Semantically Smooth Interpolation of Anisotropic MRI
Jörg Sander, Bob D. de Vos, Ivana Išgum
High-resolution medical images are beneficial for analysis but their acquisition may not always be feasible. Alternatively, high-resolution images can be created from low-resolutio…
AI for Calcium Scoring
Sanne G. M. van Velzen, Nils Hampe, Bob D. de Vos +1
Calcium scoring, a process in which arterial calcifications are detected and quantified in CT, is valuable in estimating the risk of cardiovascular disease events. Especially when…
Automatic segmentation with detection of local segmentation failures in cardiac MRI
Jörg Sander, Bob D. de Vos, Ivana Išgum
Segmentation of cardiac anatomical structures in cardiac magnetic resonance images (CMRI) is a prerequisite for automatic diagnosis and prognosis of cardiovascular diseases. To inc…
Unsupervised Super-Resolution: Creating High-Resolution Medical Images from Low-Resolution Anisotropic Examples
Jörg Sander, Bob D. de Vos, Ivana Išgum
Although high resolution isotropic 3D medical images are desired in clinical practice, their acquisition is not always feasible. Instead, lower resolution images are upsampled to h…
Deep Group-wise Variational Diffeomorphic Image Registration
Tycho F. A. van der Ouderaa, Ivana Išgum, Wouter B. Veldhuis +1
Deep neural networks are increasingly used for pair-wise image registration. We propose to extend current learning-based image registration to allow simultaneous registration of mu…
3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations
Hessam Sokooti, Bob de Vos, Floris Berendsen +5
We propose a supervised nonrigid image registration method, trained using artificial displacement vector fields (DVF), for which we propose and compare three network architectures.…