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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.

Details

Title
Vessel tech: a high-accuracy pipeline for comprehensive mouse retinal vasculature characterization
Author
Wang, Xuelin 1 ; Zhu, Guofu 2 ; Wang, Shumin 3 ; Rhen Jordan 3 ; Pang Jinjiang 3   VIAFID ORCID Logo  ; Zhang Zhengwu 1 

 University of Rochester School of Medicine and Dentistry, Department of Biostatistics and Computational Biology, Rochester, USA (GRID:grid.412750.5) (ISNI:0000 0004 1936 9166) 
 Pan-Vascular Research Institute, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Department of Cardiology, Shanghai 200072, China (GRID:grid.412750.5) 
 University of Rochester School of Medicine and Dentistry, Aab Cardiovascular Research Institute, Department of Medicine, Rochester, USA (GRID:grid.412750.5) (ISNI:0000 0004 1936 9166) 
Pages
7-11
Publication year
2021
Publication date
Feb 2021
Publisher
Springer Nature B.V.
ISSN
09696970
e-ISSN
15737209
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2494716830
Copyright
© Springer Nature B.V. 2020.