Hardware acceleration for ultra-fast Neural Network training on FPGA for MRF map reconstruction
Journal:
arXiv
Published Date:
Jun 27, 2025
Abstract
Magnetic Resonance Fingerprinting (MRF) is a fast quantitative MR Imaging
technique that provides multi-parametric maps with a single acquisition. Neural
Networks (NNs) accelerate reconstruction but require significant resources for
training. We propose an FPGA-based NN for real-time brain parameter
reconstruction from MRF data. Training the NN takes an estimated 200 seconds,
significantly faster than standard CPU-based training, which can be up to 250
times slower. This method could enable real-time brain analysis on mobile
devices, revolutionizing clinical decision-making and telemedicine.
