# Fingerprinting Orientation Distribution Functions in Diffusion MRI detects smaller crossing angles

## TL;DR

This paper introduces ODF-Fingerprinting, a novel method that improves detection of small crossing angles in diffusion MRI, enhancing the accuracy of white matter tractography and brain connectivity analysis.

## Contribution

The paper presents a fingerprinting-based approach that uses the entire ODF shape for better fiber direction detection, especially for small crossing angles, outperforming existing methods.

## Key findings

- Improved detection of small crossing angles in noisy ODFs.
- Enhanced tractography accuracy with better fiber bundle delineation.
- Maintained fiber direction precision despite noise.

## Abstract

Diffusion tractography is routinely used to study white matter architecture and brain connectivity in vivo. A key step for successful tractography of neuronal tracts is the correct identification of tract directions in each voxel. Here we propose a fingerprinting-based methodology to identify these fiber directions in Orientation Distribution Functions, dubbed ODF-Fingerprinting (ODF-FP). In ODF-FP, fiber configurations are selected based on the similarity between measured ODFs and elements in a pre-computed library. In noisy ODFs, the library matching algorithm penalizes the more complex fiber configurations. ODF simulations and analysis of bootstrapped partial and whole-brain in vivo datasets show that the ODF-FP approach improves the detection of fiber pairs with small crossing angles while maintaining fiber direction precision, which leads to better tractography results. Rather than focusing on the ODF maxima, the ODF-FP approach uses the whole ODF shape to infer fiber directions to improve the detection of fiber bundles with small crossing angle. The resulting fiber directions aid tractography algorithms in accurately displaying neuronal tracts and calculating brain connectivity.