Extending Unsupervised Neural Image Compression With Supervised Multitask Learning. - David Tellez; Diederik Höppener; Cornelis Verhoef; Dirk J. Grünhagen; Pieter Nierop; Michal Drozdzal; Jeroen van der Laak; Francesco Ciompi (MIDL, 2020)

Reproducible radiomics through automated machine learning validated on twelve clinical applications. - Martijn P. A. Starmans; Sebastian R. van der Voort; Thomas Phil; Milea J. M. Timbergen; Melissa Vos; Guillaume A. Padmos; Wouter Kessels; David Hanff; Dirk J. Grünhagen; Cornelis Verhoef; Stefan Sleijfer; Martin J. van den Bent; et al. (CoRR, 2021)

Differential Diagnosis and Molecular Stratification of Gastrointestinal Stromal Tumors on CT Images Using a Radiomics Approach. - Martijn P. A. Starmans; Milea J. M. Timbergen; Melissa Vos; Michel Renckens; Dirk J. Grünhagen; Geert J. L. H. van Leenders; Roy S. Dwarkasing; François E. J. A. Willemssen; Wiro J. Niessen; Cornelis Verhoef; Stefan Sleijfer; Jacob J. Visser; et al. (J. Digit. Imaging, 2022)

Minimally Interactive Segmentation of Soft-Tissue Tumors on CT and MRI using Deep Learning. - Douwe J. Spaanderman; Martijn P. A. Starmans; Gonnie C. M. van Erp; David F. Hanff; Judith H. Sluijter; Anne-Rose W. Schut; Geert J. L. H. van Leenders; Cornelis Verhoef; Dirk J. Grünhagen; Wiro J. Niessen; Jacob J. Visser; Stefan Klein 001 (CoRR, 2024)