Detecting delays in motor skill development of children through data analysis of a smart play device. - Jörg Sander 003; Antoine de Schipper; Annette Brons; Svetlana Mironcika; Huub Toussaint; Ben A. M. Schouten; Ben J. A. Kröse (PervasiveHealth, 2017)

Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI. - Jörg Sander 003; Bob D. de Vos; Jelmer M. Wolterink; Ivana Isgum (Image Processing, 2019)

Mutual information for unsupervised deep learning image registration. - Bob D. de Vos; Bas H. M. van der Velden; Jörg Sander 003; Kenneth G. A. Gilhuijs; Marius Staring; Ivana Isgum (Image Processing, 2020)

Automatic segmentation with detection of local segmentation failures in cardiac MRI. - Jörg Sander 003; Bob D. de Vos; Ivana Isgum (CoRR, 2020)

Unsupervised super-resolution: creating high-resolution medical images from low-resolution anisotropic examples. - Jörg Sander 003; Bob D. de Vos; Ivana Isgum (Image Processing, 2021)

Biological data annotation via a human-augmenting AI-based labeling system. - Douwe van der Wal; Iny Jhun; Israa Laklouk; Jeffrey J. Nirschl; Lara Richer; Rebecca Rojansky; Talent Theparee; Joshua Wheeler; Jörg Sander 003; Felix Y. Feng; Osama Mohamad; Silvio Savarese; et al. (npj Digit. Medicine, 2021)

Autoencoding low-resolution MRI for semantically smooth interpolation of anisotropic MRI. - Jörg Sander 003; Bob D. de Vos; Ivana Isgum (Medical Image Anal., 2022)

Deep Learning for Automatic Strain Quantification in Arrhythmogenic Right Ventricular Cardiomyopathy. - Laura Alvarez-Florez; Jörg Sander 003; Mimount Bourfiss; Fleur V. Y. Tjong; Birgitta K. Velthuis; Ivana Isgum (STACOM@MICCAI, 2023)

Reconstruction and completion of high-resolution 3D cardiac shapes using anisotropic CMRI segmentations and continuous implicit neural representations. - Jörg Sander 003; Bob D. de Vos; Steffen Bruns; Nils Planken; Max A. Viergever; Tim Leiner; Ivana Isgum (Comput. Biol. Medicine, 2023)