NigraNet: An automatic framework to assess nigral neuromelanin content in early Parkinson's disease using convolutional neural network.

ABSTRACT:

Background

Parkinson's disease (PD) demonstrates neurodegenerative changes in the substantia nigra pars compacta (SNc) using neuromelanin-sensitive (NM)-MRI. As SNc manual segmentation is prone to substantial inter-individual variability across raters, development of a robust automatic segmentation framework is necessary to facilitate nigral neuromelanin quantification. Artificial intelligence (AI) is gaining traction in the neuroimaging community for automated brain region segmentation tasks using MRI.

Objective

Developing and validating AI-based NigraNet, a fully automatic SNc segmentation framework allowing nigral neuromelanin quantification in patients with PD using NM-MRI.

Methods

We prospectively included 199 participants comprising 144 early-stage idiopathic PD

SUBMITTER: Gaurav R 

PROVIDER: S-EPMC9668659 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature