44 citations · 122 across the 5 of their papers we have counts for
5 papers
pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis
Alain Jungo, Olivier Scheidegger, Mauricio Reyes +1
Background and Objective: Deep learning enables tremendous progress in medical image analysis. One driving force of this progress are open-source frameworks like TensorFlow and PyT…
Learning Bloch Simulations for MR Fingerprinting by Invertible Neural Networks
Fabian Balsiger, Alain Jungo, Olivier Scheidegger +2
Magnetic resonance fingerprinting (MRF) enables fast and multiparametric MR imaging. Despite fast acquisition, the state-of-the-art reconstruction of MRF based on dictionary matchi…
Spatially Regularized Parametric Map Reconstruction for Fast Magnetic Resonance Fingerprinting
Fabian Balsiger, Alain Jungo, Olivier Scheidegger +3
Magnetic resonance fingerprinting (MRF) provides a unique concept for simultaneous and fast acquisition of multiple quantitative MR parameters. Despite acquisition efficiency, adop…
Learning Shape Representation on Sparse Point Clouds for Volumetric Image Segmentation
Fabian Balsiger, Yannick Soom, Olivier Scheidegger +1
Volumetric image segmentation with convolutional neural networks (CNNs) encounters several challenges, which are specific to medical images. Among these challenges are large volume…
Magnetic Resonance Fingerprinting Reconstruction via Spatiotemporal Convolutional Neural Networks
Fabian Balsiger, Amaresha Shridhar Konar, Shivaprasad Chikop +4
Magnetic resonance fingerprinting (MRF) quantifies multiple nuclear magnetic resonance parameters in a single and fast acquisition. Standard MRF reconstructs parametric maps using…