Robust Tracing and Visualization of Heterogeneous Microvascular Networks.

ABSTRACT: Advances in high-throughput imaging allow researchers to collect three-dimensional images of whole organ microvascular networks. These extremely large images contain networks that are highly complex, time consuming to segment, and difficult to visualize. In this paper, we present a framework for segmenting and visualizing vascular networks from terabyte-sized three-dimensional images collected using high-throughput microscopy. While these images require terabytes of storage, the volume devoted to the fiber network is ≈ 4 percent of the total volume size. While the networks themselves are sparse, they are tremendously complex, interconnected, and vary widely in diameter. We describe a parallel GPU-based predictor-corrector method for tracing filaments that is robust to noise and sampling er

SUBMITTER: Govyadinov PA 

PROVIDER: S-EPMC6360128 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature