Spherical convolutional neural networks can improve brain microstructure estimation from diffusion MRI data

arXiv:2211.09887v3 Announce Type: replace-cross
Abstract: Diffusion magnetic resonance imaging is sensitive to the microstructural properties of brain tissue. However, estimating clinically and scientifically relevant microstructural properties from the measured signals remains a highly challenging inverse problem that machine learning may help solve. This study investigated if recently developed rotationally invariant spherical convolutional neural networks can improve microstructural parameter estimation. We trained a spherical convolutional neural network to predict the ground-truth parameter values from efficiently simulated noisy data and applied the …

abstract arxiv brain convolutional neural networks cs.lg data diffusion eess.iv imaging machine machine learning mri networks neural networks physics.med-ph solve study type