An image analysis toolbox for 3D vascular tracing and network topology

被引:0
|
作者
Cudmore, Robert H. [1 ]
Zawadzki, Robert J. [2 ,3 ]
机构
[1] Univ Calif Davis, Dept Physiol & Membrane Biol, Sch Med, Davis, CA 95616 USA
[2] Univ Calif Davis, Dept Cell Biol & Human Anat, UC Davis EyePod Small Anim Ocular Imaging Lab, Davis, CA USA
[3] Univ Calif Davis, Dept Ophthalmol & Vis Sci, UC Davis Eye Ctr, Davis, CA USA
关键词
optical coherence tomography angiography; image analysis; analysis software; !text type='python']python[!/text; graphical user interface;
D O I
10.1117/12.3001224
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Proper vascular structure and function is critical to maintain healthy tissue. Vascular dysfunction is a hallmark in a number of diseases including but not limited to Alzheimer's disease, diabetes, hypertension, and the normal process of aging. It has become clear than an early biomarker for these disparate diseases is dysfunction in retinal vascular structure and function. There is a growing computational toolbox for the analysis of vascular networks yet there are few easy to use graphical-user-interfaces that bring these tools to mere biologists. Here we present a suite of graphical-user-interfaces for the tracing, curation, and analysis of retinal vascular networks from 3D imaging datasets. The goal of these tools is to provide the needed link between continual advances in computational analysis with easy to use graphical-user-interfaces that will allow ground-truth results. We present an analysis of optical coherence tomography angiography (OCTA) images acquired in mice in vivo.
引用
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页数:9
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