| Literature DB >> 33033849 |
Xuelin Wang1, Guofu Zhu2, Shumin Wang3, Jordan Rhen3, Jinjiang Pang4, Zhengwu Zhang5.
Abstract
Mouse retinal vasculature is a well-recognized and commonly used animal model for angiogenesis and microvascular remodeling. Morphological features of retinal vasculature reflect the vessel's biological functions, and are critical in understanding the physiological and pathological process of vascular development and disease. Here we developed a comprehensive software, Vessel Tech, using retinal vasculature images of postnatal mice. This pipeline can automatically process retinal vascular images, reconstruct vessel network with high accuracy and assess global and local vascular characteristics based on the recent machine-learning techniques. The development of Vessel Tech provides a powerful tool for vascular biologists.Entities:
Keywords: Automatic quantification; Deep learning; Morphologic analysis; Mouse retinal vasculature; Vascular development
Mesh:
Year: 2020 PMID: 33033849 PMCID: PMC7920901 DOI: 10.1007/s10456-020-09752-8
Source DB: PubMed Journal: Angiogenesis ISSN: 0969-6970 Impact factor: 10.658