Head Tissue Template

MethodThe method of Brudfors et. al. (2020) was used to construct a tissue probability map from T2-weighted and PD-weighted scans of the first 64 subjects from the IXI dataset, along with the T1-weighted scans of the next 64 IXI subjects. The 15 training subjects' scans from the MICCAI Challenge Dataset were also included in the template construction. Default settings were used throughout, except for the regularisation for the diffeomorphic registration, which was set to be higher than the default settings (``Shape Regularisation'' on the user interface was set to [0.0001 0.5 0.5 0.0 1.0]). After merging several of the automatically identified tissue classes, the tissue probability map has 1 mm isotropic resolution, dimensions of 191x243x229 voxels and consists of 11 tissue types, three of which approximately correspond with brain tissues.This image (roughly) contains the logarithms of the tissue probabilities, which can be recovered using a softmax (exp(mu)/(sum(exp(mu)+1)).ReferenceBrudfors M, Balbastre Y, Flandin G, Nachev P, Ashburner J. Flexible Bayesian Modelling for Nonlinear Image Registration. In International Conference on Medical Image Computing and Computer-Assisted Intervention 2020 Oct 4 (pp. 253-263). Springer, Cham.