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RAC-CNN: multimodal deep learning based automatic detection and classification of rod and cone photoreceptors in adaptive optics scanning light ophthalmoscope images

Quantification of the human rod and cone photoreceptor mosaic in adaptive optics scanning light ophthalmoscope (AOSLO) images is useful for the study of various retinal pathologies. Subjective and time-consuming manual grading has remained the gold standard for evaluating these images, with no well...

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Библиографические подробности
Опубликовано в: :Biomed Opt Express
Главные авторы: Cunefare, David, Huckenpahler, Alison L., Patterson, Emily J., Dubra, Alfredo, Carroll, Joseph, Farsiu, Sina
Формат: Artigo
Язык:Inglês
Опубликовано: Optical Society of America 2019
Предметы:
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC6701534/
https://ncbi.nlm.nih.gov/pubmed/31452977
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1364/BOE.10.003815
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