Brief

Researchers have developed TractFM, a novel foundation model designed to learn representations directly from diffusion MRI tractograms. This model uniquely combines a local streamline encoder with a permutation-equivariant tractogram encoder, enabling it to process all streamlines from a subject simultaneously. By pretraining on anatomical parcellation, TractFM generates reusable embeddings for both individual streamlines and compact subject-level descriptors. The model demonstrates strong generalization capabilities, achieving accurate tract parcellation and predicting subject phenotypes like age and sex across different tractography algorithms and datasets. AI