TriSAM: Tri-Plane SAM for zero-shot cortical blood vessel segmentation in VEM images

arXiv:2401.13961v2 Announce Type: replace
Abstract: While imaging techniques at macro and mesoscales have garnered substantial attention and resources, microscale VEM imaging, capable of revealing intricate vascular details, has lacked the necessary benchmarking infrastructure. In this paper, we address a significant gap in the field of neuroimaging by introducing the largest-to-date public benchmark, \textbf{BvEM}, designed specifically for cortical blood vessel segmentation in volume electron microscopy (VEM) images. Our BvEM benchmark is based on VEM image volumes from three mammal species: adult …

abstract arxiv attention benchmarking cs.cv gap images imaging infrastructure macro neuroimaging paper plane resources sam segmentation type zero-shot