Vessel network extraction and analysis of mouse pulmonary vasculature via X-ray micro-computed tomographic imaging.

ABSTRACT: In this work, non-invasive high-spatial resolution three-dimensional (3D) X-ray micro-computed tomography (μCT) of healthy mouse lung vasculature is performed. Methodologies are presented for filtering, segmenting, and skeletonizing the collected 3D images. Novel methods for the removal of spurious branch artefacts from the skeletonized 3D image are introduced, and these novel methods involve a combination of distance transform gradients, diameter-length ratios, and the fast marching method (FMM). These new techniques of spurious branch removal result in the consistent removal of spurious branches without compromising the connectivity of the pulmonary circuit. Analysis of the filtered, skeletonized, and segmented 3D images is performed using a newly developed Vessel Network Extraction algo

SUBMITTER: Chadwick EA 

PROVIDER: S-EPMC8594947 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature