1 research outputs found
Automated segmentation of the locus coeruleus from neuromelanin-sensitive 3t MRI using deep convolutional neural networks
The locus coeruleus (LC) is a small brain structure in the
brainstem that may play an important role in the pathogenesis of Alzheimer’s Disease (AD) and Parkinson’s Disease (PD). The majority of studies to date have relied on using manual segmentation methods to segment
the LC, which is time consuming and leads to substantial interindividual
variability across raters. Automated segmentation approaches might be
less error-prone leading to a higher consistency in Magnetic Resonance
Imaging (MRI) contrast assessments of the LC across scans and studies.
The objective of this study was to investigate whether a convolutional
neural network (CNN)-based automated segmentation method allows for
reliably delineating the LC in in vivo MR images. The obtained results
indicate performance superior to the inter-rater agreement, i.e. approximately 70% Dice similarity coefficient (DSC)