# Anatomy-guided fiber trajectory distribution estimation for cranial nerves tractography

arXiv: https://arxiv.org/abs/2402.18856 · HTML: https://mlsanity.com/paper/2402.18856/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 19 references that are in the map.
- First posted on arXiv 29 Feb 2024.

## Builds on (most cited first, 1 of 1)

- [Combined tract segmentation and orientation mapping for bundle-specific tractography](https://mlsanity.com/paper/1901.10271/) (2019)

## Built on by (most cited first, 2 of 2)

- [Automated Mapping the Pathways of Cranial Nerve II, III, V, and VII/VIII: A Multi-Parametric Multi-Stage Diffusion Tractography Atlas](https://mlsanity.com/paper/2507.23245/) (2025)
- [Tractography-Guided Dual-Label Collaborative Learning for Multi-Modal Cranial Nerves Parcellation](https://mlsanity.com/paper/2508.01577/) (2025)

## Abstract (arXiv)

Diffusion MRI tractography is an important tool for identifying and analyzing the intracranial course of cranial nerves (CNs). However, the complex environment of the skull base leads to ambiguous spatial correspondence between diffusion directions and fiber geometry, and existing diffusion tractography methods of CNs identification are prone to producing erroneous trajectories and missing true positive connections. To overcome the above challenge, we propose a novel CNs identification framework with anatomy-guided fiber trajectory distribution, which incorporates anatomical shape prior knowledge during the process of CNs tracing to build diffusion tensor vector fields. We introduce higher-order streamline differential equations for continuous flow field representations to directly characterize the fiber trajectory distribution of CNs from the tract-based level. The experimental results on the vivo HCP dataset and the clinical MDM dataset demonstrate that the proposed method reduces false-positive fiber production compared to competing methods and produces reconstructed CNs (i.e. CN II, CN III, CN V, and CN VII/VIII) that are judged to better correspond to the known anatomy.