ANALYSIS OF SURFACE-BASED MORPHOMETRIC OF HIPPOCAMPAL SUBFIELD VOLUMETRY IN ALZHEIMER'S DISEASE AND MCI

Background: Changes in Hippocampal subfield volume of patients with Alzheimer's Disease and Mild Cognitive Impairment from structural Magnetic Resonance Imaging using the techniques like free surfer and FIRST. The Hippocampus is one of the main areas used in neuroimaging studies. Hippocampus is responsible for memory and learning because of which it can be considered as one among the important biomarker for the neuro diseases. Hippocampal subfield even though being an important region for diagnosis of the AD diseases, is not being used in most of the study because of the complexities such as semi-automated segmentation and manual segmentation. Methods: To overcome existing problems we have modeled a novel subfield segmentation pipeline which consists of three stages. Those are Subfield information extraction, hippocampal segmentation and atlas mean surface calculation. Results: Experimental implementation on ADNI dataset it is proved that our model provides high accuracy than the other models comparatively for diagnosing the disease. Conclusions: Our proposed approach successfully analyzed the hippocampus subfield volume from MRI scan for AD and MCI disease.