干旱区生态环境知识资源中心

This work intends to predict the clinical dementia rating (CDR) based on human brain volumetric segmentation measures from magnetic resonance (MR) images. These brain measures were extracted using an automated image segmentation method based on morphometry study and considering brain anatomical atlas. The prediction was achieved by Bayesian classifier. The classifier training was performed on 371 individuals from Open Access Series of Imaging Studies (OASIS) dataset. MR images and clinical information (including the Clinical Dementia Rating score) of each case are available oil OASIS dataset. Experimentation results were assessed using true-positive rate. The final purpose of this work is to design a computer-aided diagnostic system that could be able to detect precociously neurodegenerative disorders, allowing early therapeutic interventions.