This repository aims to provide a versatile Bloch solver for simulating MR signal evolution for samples with arbitrary NMR spectra and parameters in the presence of field inhomogeneities and spatial variation.

The Bloch solver components are designed to accomodate scalar-, vector-, and matrix-fields. The scalar/vector/matrix part always occupies the first two dimensions of an array, and any subsequent variable (e.g., spatial dimensions, spectroscopic dimension) vary along the remaining dimensions. For example, if we model a 1D object that has varying T1 along the x-axis, the T1 field would have shape (1,1,Nx) (scalar field) and the position field would have shape (3,1,Nx) (vector field), with the x-component (row 1) reflecting the sample points along x.

The code used to generate simulated configuration state imaging data in our paper is available in the sample directory.

• Adams-Tew, S.I. et al. (2024). Physics Informed Neural Networks for Estimation of Tissue Properties from Multi-echo Configuration State MRI. In: Linguraru, M.G., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. MICCAI 2024. Lecture Notes in Computer Science, vol 15011. Springer, Cham. https://doi.org/10.1007/978-3-031-72120-5_47