NORHA: A NORmal Hippocampal Asymmetry Deviation Index Based on One-Class Novelty Detection and 3D Shape Features.

Radiologists routinely analyze hippocampal asymmetries in magnetic resonance (MR) images as a biomarker for neurodegenerative conditions like epilepsy and Alzheimer's Disease. However, current clinical tools rely on either subjective evaluations, basic volume measurements, or disease-specific models that fail to capture more complex differences in normal shape. In this paper, we overcome these limitations by introducing NORHA, a novel NORmal Hippocampal Asymmetry deviation index that uses machine learning novelty detection to objectively quantify it from MR scans.

VBM sensitivity to localization and extent of mouse brain lesions: A simulation approach.

Background And Objectives: Voxel-based morphometry (VBM) is a popular neuroimaging technique, used to detect and quantify morphological differences in brain tissues between groups. Widely used in human studies, VBM approaches have tremendous potential for neuroimaging studies in animal models. A significant challenge for applying VBM to small animal studies is the poor understanding of how the design of preprocessing pipelines impacts quantitative results.