A MATLAB package for automatic extraction of flow index in OCT-A images by intelligent vessel manipulation

Abstract

Optical Coherence Tomography Angiography (OCT-A) is regarded as a non-invasive approach for imaging the blood vessels. New investigations on OCT-A are developed to extract structural features useful in the diagnosis and treatment of ocular diseases. Raw OCT-A is capable of providing qualitative microvascular data, but our mentioned features are intended to provide quantitative information and trustable comparison during follow ups and between different people. In this paper, we proposed an easy-to-use software to remove spurious blood vessel shadows and extract numerical features from OCT-A images. The features are expected to play an important role in the diagnosis and understanding of blood conditions. For this purpose, we used blood flow information as vessel density (VD) map () in a 4.5x4.5 mm rectangle scan centered on the optic disk for deep optic nerve data. Information from original image and image with small vessels were measured in whole-image (WI), peripapillary (PP) areas and theirs superior and inferior sectors. Furthermore, we also used blood flow information at parafoveal capillary as VD map in order to remove the projection artifact of superficial macular vessels from deep macular images, compatible with different analysis protocols for macula (3x3, 4x4, 5x5, 6x6, and 7x7 mm). Similarly, information from whole image and small vessels were measured in whole-image (Wi) and sector-based parafovea areas. (C) 2020 The Authors. Published by Elsevier B.V.