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 errors common in these data sets. We also propose a number of visualization techniques designed to convey the complex statistical descriptions of fibers across large tissue sections-including commonly studied microvascular characteristics, such as orientation and volume.
Subject(s)
Imaging, Three-Dimensional/methods , Microvessels/diagnostic imaging , Algorithms , Animals , Brain/blood supply , Brain/diagnostic imaging , Computer Graphics , Mice , MicroscopyABSTRACT
The IEEE Transactions on Visualization and Computer Graphics (TVCG) November 2016 issue, contains a special section featuring papers presented at the IEEE International Symposium on Mixed and Augmented Reality 2016. Unfortunately, the welcome message contributed by the guest editors of this special section, Wolfgang Broll, Hideo Saito, and J. Edward Swan II, was accidentially omitted. The November 2017 issue of TVCG is a special issue featuring papers presented at the IEEE International Symposium on Mixed and Augmented Reality 2017. Under similar circumstances as mentioned above, the welcome message contributed by the guest editors of this special issue, Wolfgang Broll, Holger Regenbrecht, and J. Edward Swan II, was accidentially omitted. We include both messages in the following, with apologies to the guest editors and our readers. Dieter Schmalstieg Associate Editor-in-Chief, TVCG For information.
