12 citations · 15 across the 2 of their papers we have counts for
4 papers
CBCT-to-CT synthesis with a single neural network for head-and-neck, lung and breast cancer adaptive radiotherapy
Matteo Maspero, Mark HF Savenije, Tristan CF van Heijst +4
Purpose: CBCT-based adaptive radiotherapy requires daily images for accurate dose calculations. This study investigates the feasibility of applying a single convolutional network t…
Deep learning brain conductivity mapping using a patch-based 3D U-net
Nils Hampe, Ulrich Katscher, Cornelis A. T. van den Berg +2
Purpose: To investigate deep learning electrical properties tomography (EPT) for application on different simulated and in-vivo datasets including pathologies for obtaining quantit…
Dictionary-free MR Fingerprinting reconstruction of balanced-GRE sequences
Alessandro Sbrizzi, Tom Bruijnen, Oscar van der Heide +2
Magnetic resonance fingerprinting (MRF) can successfully recover quantitative multi-parametric maps of human tissue in a very short acquisition time. Due to their pseudo-random nat…
Deep MR to CT Synthesis using Unpaired Data
Jelmer M. Wolterink, Anna M. Dinkla, Mark H. F. Savenije +3
MR-only radiotherapy treatment planning requires accurate MR-to-CT synthesis. Current deep learning methods for MR-to-CT synthesis depend on pairwise aligned MR and CT training ima…