Centre de Recherche Hôpital Maisonneuve-Rosemont, Montréal, QC, Canada.
Département d'Ophtalmologie, Université de Montréal, Montréal, QC, Canada.
Sci Rep. 2017 Feb 9;7:42112. doi: 10.1038/srep42112.
The use of optical coherence tomography (OCT) to study ocular diseases associated with choroidal physiology is sharply limited by the lack of available automated segmentation tools. Current research largely relies on hand-traced, single B-Scan segmentations because commercially available programs require high quality images, and the existing implementations are closed, scarce and not freely available. We developed and implemented a robust algorithm for segmenting and quantifying the choroidal layer from 3-dimensional OCT reconstructions. Here, we describe the algorithm, validate and benchmark the results, and provide an open-source implementation under the General Public License for any researcher to use (https://www.mathworks.com/matlabcentral/fileexchange/61275-choroidsegmentation).
光学相干断层扫描(OCT)在研究与脉络膜生理学相关的眼部疾病方面的应用受到缺乏可用的自动分割工具的严重限制。当前的研究在很大程度上依赖于手动追踪的单个 B 扫描分割,因为商业上可用的程序需要高质量的图像,而现有的实现是封闭的、稀缺的且无法自由获取。我们开发并实现了一种从 3D OCT 重建中分割和量化脉络膜层的强大算法。在这里,我们描述了该算法,并验证和基准测试了结果,并在通用公共许可证下提供了一个开源实现,供任何研究人员使用(https://www.mathworks.com/matlabcentral/fileexchange/61275-choroidsegmentation)。