Cross-site harmonization of diffusion MRI data without matched training subjects.

ABSTRACT:

Purpose

Diffusion MRI (dMRI) data typically suffer of significant cross-site variability, which prevents naively performing pooled analyses. To attenuate cross-site variability, harmonization methods such as the rotational invariant spherical harmonics (RISH) have been introduced to harmonize the dMRI data at the signal level. A common requirement of the RISH method is the availability of healthy individuals who are matched at the group level, which may not always be readily available, particularly retrospectively. In this work, we propose a framework to harmonize dMRI without matched training groups.

Methods

Our framework learns harmonization features while controlling for potential covariates using a voxel-based generalized linear model (GLM). RISH-GLM allows us to simulta

SUBMITTER: De Luca A 

PROVIDER: S-EPMC12309894 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature