52 citations · 68 across the 5 of their papers we have counts for
5 papers
Deep Learning for Automatic Strain Quantification in Arrhythmogenic Right Ventricular Cardiomyopathy
Laura Alvarez-Florez, Jörg Sander, Mimount Bourfiss +3
Quantification of cardiac motion with cine Cardiac Magnetic Resonance Imaging (CMRI) is an integral part of arrhythmogenic right ventricular cardiomyopathy (ARVC) diagnosis. Yet, t…
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…
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…
Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI
Jörg Sander, Bob D. de Vos, Jelmer M. Wolterink +1
Current state-of-the-art deep learning segmentation methods have not yet made a broad entrance into the clinical setting in spite of high demand for such automatic methods. One imp…