Radiomics-Based Artificial Intelligence Differentiation of Neurodegenerative Diseases with Reference to the Volumetry.

ABSTRACT: This study aimed to build automated detection models-one by brain regional volume (V-model), and the other by radiomics features of the whole brain (R-model)-to differentiate mild cognitive impairment (MCI) from cognitive normal (CN), and Alzheimer's Disease (AD) from mild cognitive impairment (MCI). The objectives are to compare the models and identify whether radiomics or volumetry can provide a better prediction for differentiating different types of dementia. 582 MRI T1-weighted images were retrieved from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, which is a multicenter operating open source database for AD. In total, 97 images of AD, 293 images of MCI patient and 192 images of cognitive normal were divided into a training, a validation and a test group at a ratio

SUBMITTER: Cheung EYW 

PROVIDER: S-EPMC9024778 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature