Novel segmentation algorithm for high-throughput analysis of spectral domain-optical coherence tomography imaging of teleost retinas
Novel segmentation algorithm for high-throughput analysis of spectral domain-optical coherence tomography imaging of teleost retinas
复制标题
用于硬骨鱼视网膜谱域光学相干断层扫描成像高通量分析的新型分割算法
作者：
Kent R. Barter;H. Paradis;R. Gendron;Josué Vidal;Oscar Meruvia
谱域光学相干断层扫描 (SD-OCT) 已成为评估活体受试者眼组织以及开展眼发育、健康和疾病研究的重要工具。由于缺乏自动化分析程序，SD-OCT 图像（尤其是非哺乳动物物种的图像）的处理是一个劳动密集型的手动过程。本文介绍了一种新颖的计算机算法的开发和实施，用于对活体硬骨鱼眼睛的 SD-OCT 图像进行定量分析。使用基于阈值的新颖算法开发了视网膜层 SD-OCT 图像的自动分割处理。该算法可在短时间内测量硬骨鱼眼部结构的大量成像数据中的视网膜厚度特征，与手动测量相比，提高了 SD-OCT 图像分析的准确性和可重复性。该算法还为给定数据集的大量图像生成数百个视网膜厚度测量值。同时，还创建了将 SD-OCT 图像测量结果绘制为颜色梯度的热图软件。该软件直接转换每个处理图像的测量值，以表示整个视网膜扫描的厚度变化。它还可以在整个扫描过程中实现视网膜厚度的 2D 和 3D 可视化，从而促进样本比较和感兴趣区域的定位。研究结果表明，新算法比手动 SD-OCT 分析更准确、可靠且可重复。该算法的适应性使其可能适用于分析其他非哺乳动物物种的 SD-OCT 扫描。
Spectral domain-optical coherence tomography (SD-OCT) has become an essential tool for assessing ocular tissues in live subjects and conducting research on ocular development, health, and disease. The processing of SD-OCT images, particularly those from non-mammalian species, is a labor-intensive manual process due to a lack of automated analytical programs. This paper describes the development and implementation of a novel computer algorithm for the quantitative analysis of SD-OCT images of live teleost eyes. Automated segmentation processing of SD-OCT images of retinal layers was developed using a novel algorithm based on thresholding. The algorithm measures retinal thickness characteristics in a large volume of imaging data of teleost ocular structures in a short time, providing increased accuracy and repeatability of SD-OCT image analysis over manual measurements. The algorithm also generates hundreds of retinal thickness measurements per image for a large number of images for a given dataset. Meanwhile, heat mapping software that plots SD-OCT image measurements as a color gradient was also created. This software directly converts the measurements of each processed image to represent changes in thickness across the whole retinal scan. It also enables 2D and 3D visualization of retinal thickness across the scan, facilitating specimen comparison and localization of areas of interest. The study findings showed that the novel algorithm is more accurate, reliable, and repeatable than manual SD-OCT analysis. The adaptability of the algorithm makes it potentially suitable for analyzing SD-OCT scans of other non-mammalian species.
影响因子：
3.4
作者：
Bell, Brent A.;Yuan, Alex;Dicicco, Rose M.;Fogerty, Joseph;Lessieur, Emma M.;Perkins, Brian D.
通讯作者：
Perkins, Brian D.
影响因子：
3.4
作者：
Srinivasan, Pratul P.;Heflin, Stephanie J.;Farsiu, Sina
通讯作者：
Farsiu, Sina