Repeatability of binarization thresholding methods for optical coherence tomography angiography image quantification

Author:

Mehta Nihaal,Braun Phillip X.,Gendelman IsaacORCID,Alibhai A. Yasin,Arya Malvika,Duker Jay S.,Waheed Nadia K.

Abstract

AbstractBinarization is a critical step in analysis of retinal optical coherence tomography angiography (OCTA) images, but the repeatability of metrics produced from various binarization methods has not been fully assessed. This study set out to examine the repeatability of OCTA quantification metrics produced using different binarization thresholding methods, all of which have been applied in previous studies, across multiple devices and plexuses. Successive 3 × 3 mm foveal OCTA images of 13 healthy eyes were obtained on three different devices. For each image, contrast adjustments, 3 image processing techniques (linear registration, histogram normalization, and contrast-limited adaptive histogram equalization), and 11 binarization thresholding methods were independently applied. Vessel area density (VAD) and vessel length were calculated for retinal vascular images. Choriocapillaris (CC) images were quantified for VAD and flow deficit metrics. Repeatability, measured using the intra-class correlation coefficient, was inconsistent and generally not high (ICC < 0.8) across binarization thresholds, devices, and plexuses. In retinal vascular images, local thresholds tended to incorrectly binarize the foveal avascular zone as white (i.e., wrongly indicating flow). No image processing technique analyzed consistently resulted in highly repeatable metrics. Across contrast changes, retinal vascular images showed the lowest repeatability and CC images showed the highest.

Funder

Yale School of Medicine Medical Student Fellowship

Macula Vision Research Foundation

U.S. Department of Health & Human Services | National Institutes of Health

United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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