Automated peripheral nerve segmentation for MR-neurography.

ABSTRACT:

Background

Magnetic resonance neurography (MRN) is increasingly used as a diagnostic tool for peripheral neuropathies. Quantitative measures enhance MRN interpretation but require nerve segmentation which is time-consuming and error-prone and has not become clinical routine. In this study, we applied neural networks for the automated segmentation of peripheral nerves.

Methods

A neural segmentation network was trained to segment the sciatic nerve and its proximal branches on the MRN scans of the right and left upper leg of 35 healthy individuals, resulting in 70 training examples, via 5-fold cross-validation (CV). The model performance was evaluated on an independent test set of one-sided MRN scans of 60 healthy individuals.

Results

Mean Dice similarity coefficient (DS

SUBMITTER: Beste NC 

PROVIDER: S-EPMC11347527 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature