Macular hole morphology and measurement using an automated three-dimensional image segmentation algorithm

OBJECTIVE: Full-thickness macular holes (MH) are classified principally by size, which is one of the strongest predictors of anatomical and visual success. Using a three-dimensional (3D) automated image processing algorithm, we analysed optical coherence tomography (OCT) images of 104 MH of patients...

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Bibliografiska uppgifter
I publikationen:BMJ Open Ophthalmol
Huvudupphovsmän: Chen, Yunzi, Nasrulloh, Amar V, Wilson, Ian, Geenen, Caspar, Habib, Maged, Obara, Boguslaw, Steel, David H W
Materialtyp: Artigo
Språk:Inglês
Publicerad: BMJ Publishing Group 2020
Ämnen:
Original Research
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC7430427/
https://ncbi.nlm.nih.gov/pubmed/32844119
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1136/bmjophth-2019-000404
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