AI RESEARCH
VAMAE: Vessel-Aware Masked Autoencoders for OCT Angiography
arXiv CS.CV
•
ArXi:2604.06583v1 Announce Type: new Optical coherence tomography angiography (OCTA) provides non-invasive visualization of retinal microvasculature, but learning robust representations remains challenging due to sparse vessel structures and strong topological constraints. Many existing self-supervised learning approaches, including masked autoencoders, are primarily designed for dense natural images and rely on uniform masking and pixel-level reconstruction, which may inadequately capture vascular geometry.