Greater accuracy of radiomics compared to deep learning to discriminate normal subjects from patients with dementia: a whole brain 18FDG PET analysis.
Journal:
Nuclear medicine communications
Published Date:
Feb 19, 2024
Abstract
METHODS: 18F-FDG brain PET and clinical score were collected in 85 patients with dementia and 125 healthy controls (HC). Patients were assigned to various form of dementia on the basis of clinical evaluation, follow-up and voxels comparison with HC using a two-sample Student's t -test, to determine the regions of brain involved. Radiomic analysis was performed on the whole brain after normalization to an optimized template. After feature selection using the minimum redundancy maximum relevance method and Pearson's correlation coefficients, a Neural Network model was tested to find the accuracy to classify HC and demented patients. Twenty subjects not included in the training were used to test the models. The results were compared with those obtained by conventional CNN model.