"Novel nested patch-based feature extraction model for automated Parkin" by Ela Kaplan, Erman Altunisik et al.
Objective: Parkinson's disease (PD) is a common neurological disorder with variable clinical manifestations and magnetic resonance imaging (MRI) findings. We propose a handcrafted image classification model that can accurately (i) classify different PD stages, (ii) detect comorbid dementia, and (iii) discriminate PD-related motor symptoms. Methods: Selected image datasets from three PD studies were used to develop the classification model. Our proposed novel automated system was developed i...
Image Classification Local Binary Pattern Ocal Phase Quantization Eighborhood Component Analysis Ested Patch Division D Image Classification
Source: uow.edu.au