Abstract
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).
Cite
CITATION STYLE
Mazzaferri, J., Beaton, L., Hounye, G., Sayah, D. N., & Costantino, S. (2017). Open-source algorithm for automatic choroid segmentation of OCT volume reconstructions. Scientific Reports, 7. https://doi.org/10.1038/srep42112
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