OCTAVA: an open-source toolbox for quantitative analysis of optical
coherence tomography angiography images
- URL: http://arxiv.org/abs/2109.01835v1
- Date: Sat, 4 Sep 2021 10:11:42 GMT
- Title: OCTAVA: an open-source toolbox for quantitative analysis of optical
coherence tomography angiography images
- Authors: Gavrielle R. Untracht, Rolando Matos, Nikolaos Dikaios, Mariam Bapir,
Abdullah K. Durrani, Teemapron Butsabong, Paola Campagnolo, David D. Sampson,
Christian Heiss and Danuta M. Sampson
- Abstract summary: We report a user-friendly, open-source toolbox, OCTAVA, to automate the pre-processing, segmentation, and quantitative analysis of en face OCTA maximum intensity projection images.
We perform quantitative analysis of OCTA images from different commercial and non-commercial instruments and samples and show OCTAVA can accurately and reproducibly determine metrics for characterization of microvasculature.
- Score: 0.2621533844622817
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Optical coherence tomography angiography (OCTA) performs non-invasive
visualization and characterization of microvasculature in research and clinical
applications mainly in ophthalmology and dermatology. A wide variety of
instruments, imaging protocols, processing methods and metrics have been used
to describe the microvasculature, such that comparing different study outcomes
is currently not feasible. With the goal of contributing to standardization of
OCTA data analysis, we report a user-friendly, open-source toolbox, OCTAVA
(OCTA Vascular Analyzer), to automate the pre-processing, segmentation, and
quantitative analysis of en face OCTA maximum intensity projection images in a
standardized workflow. We present each analysis step, including optimization of
filtering and choice of segmentation algorithm, and definition of metrics. We
perform quantitative analysis of OCTA images from different commercial and
non-commercial instruments and samples and show OCTAVA can accurately and
reproducibly determine metrics for characterization of microvasculature. Wide
adoption could enable studies and aggregation of data on a scale sufficient to
develop reliable microvascular biomarkers for early detection, and to guide
treatment, of microvascular disease.
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