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Open-source algorithm for automatic choroid segmentation of OCT volume reconstructions

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 re...

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Detalles Bibliográficos
Autores principales: Mazzaferri, Javier, Beaton, Luke, Hounye, Gisèle, Sayah, Diane N., Costantino, Santiago
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5299605/
https://www.ncbi.nlm.nih.gov/pubmed/28181546
http://dx.doi.org/10.1038/srep42112
Descripción
Sumario: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).