Ricci flow-based brain surface covariance descriptors for Alzheimer disease

arXiv:2403.06645v1 Announce Type: cross
Abstract: Automated feature extraction from MRI brain scans and diagnosis of Alzheimer's disease are ongoing challenges. With advances in 3D imaging technology, 3D data acquisition is becoming more viable and efficient than its 2D counterpart. Rather than using feature-based vectors, in this paper, for the first time, we suggest a pipeline to extract novel covariance-based descriptors from the cortical surface using the Ricci energy optimization. The covariance descriptors are components of the nonlinear manifold of symmetric …

abstract acquisition advances alzheimer's arxiv automated brain challenges covariance cs.cv cs.lg data diagnosis disease eess.iv extraction feature feature extraction flow imaging mri paper scans surface technology type vectors