GenTract: Generative Global Tractography

TL;DR

GenTract is a novel generative model for global brain tractography from dMRI data, significantly improving accuracy and robustness over existing methods, especially in noisy or low-resolution scenarios.

Contribution

It introduces the first generative approach to global tractography, directly mapping dMRI to anatomically plausible streamlines, outperforming state-of-the-art baselines.

Findings

GenTract achieves 2.1x higher precision than TractOracle.

It outperforms competitors by an order of magnitude in noisy, low-resolution data.

Produces high-quality tractograms suitable for research and imperfect data.

Abstract

Tractography is the process of inferring the trajectories of white-matter pathways in the brain from diffusion magnetic resonance imaging (dMRI). Local tractography methods, which construct streamlines by following local fiber orientation estimates stepwise through an image, are prone to error accumulation and high false positive rates, particularly on noisy or low-resolution data. In contrast, global methods, which attempt to optimize a collection of streamlines to maximize compatibility with underlying fiber orientation estimates, are computationally expensive. To address these challenges, we introduce GenTract, the first generative model for global tractography. We frame tractography as a generative task, learning a direct mapping from dMRI to complete, anatomically plausible streamlines. We compare both diffusion-based and flow matching paradigms and evaluate GenTract's performance against state-of-the-art baselines. Notably, GenTract achieves precision 2.1x higher than the next-best method, TractOracle. This advantage becomes even more pronounced in challenging low-resolution and noisy settings, where it outperforms the closest competitor by an order of magnitude. By producing tractograms with high precision on research-grade data while also maintaining reliability on imperfect, lower-resolution data, GenTract represents a promising solution for global tractography.