V2C-Long: Longitudinal Cortex Reconstruction with Spatiotemporal Correspondence

arXiv:2402.17438v1 Announce Type: cross
Abstract: Reconstructing the cortex from longitudinal MRI is indispensable for analyzing morphological changes in the human brain. Despite the recent disruption of cortical surface reconstruction with deep learning, challenges arising from longitudinal data are still persistent. Especially the lack of strong spatiotemporal point correspondence hinders downstream analyses due to the introduced noise. To address this issue, we present V2C-Long, the first dedicated deep learning-based cortex reconstruction method for longitudinal MRI. In contrast to existing methods, V2C-Long …

abstract arxiv brain challenges cortex cs.cv data deep learning disruption eess.iv human mri surface type