Multi-model sequential analysis of MRI data for microstructure prediction in heterogeneous tissue.

ABSTRACT: We propose a general method for combining multiple models to predict tissue microstructure, with an exemplar using in vivo diffusion-relaxation MRI data. The proposed method obviates the need to select a single 'optimum' structure model for data analysis in heterogeneous tissues where the best model varies according to local environment. We break signal interpretation into a three-stage sequence: (1) application of multiple semi-phenomenological models to predict the physical properties of tissue water pools contributing to the observed signal; (2) from each Stage-1 semi-phenomenological model, application of a tissue microstructure model to predict the relative volumes of tissue structure components that make up each water pool; and (3) aggregation of the predictions of tissue structure,

SUBMITTER: Enriquez-Mier-Y-Teran FE 

PROVIDER: S-EPMC10543593 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature