Quantifying Neurodegenerative Progression With DeepSymNet, an End-to-End Data-Driven Approach.

ABSTRACT: Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide and is one of the leading sources of morbidity and mortality in the aging population. There is a long preclinical period followed by mild cognitive impairment (MCI). Clinical diagnosis and the rate of decline is variable. Progression monitoring remains a challenge in AD, and it is imperative to create better tools to quantify this progression. Brain magnetic resonance imaging (MRI) is commonly used for patient assessment. However, current approaches for analysis require strong a priori assumptions about regions of interest used and complex preprocessing pipelines including computationally expensive non-linear registrations and iterative surface deformations. These preprocessing steps are composed of many stack

SUBMITTER: Pena D 

PROVIDER: S-EPMC6788344 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature