2 papers
physics.med-ph2026
Data-driven Synthesis of Magnetic Resonance Spectroscopy Data using a Variational Autoencoder
Dennis M. J. van de Sande, Julian P. Merkofer, Sina Amirrajab +4
The development of deep learning methods for magnetic resonance spectroscopy (MRS) is often hindered by limited availability of large, high-quality training datasets. While physics…
physics.med-ph2025
A Digital Phantom for MR Spectroscopy Data Simulation
D. M. J. van de Sande, A. T. Gudmundson, S. Murali-Manohar +9
Simulated data is increasingly valued by researchers for validating MRS processing and analysis algorithms. However, there is no consensus on the optimal approaches for simulation…