Deep learning-based algorithm for the detection of idiopathic full thickness macular holes in spectral domain optical coherence tomography

Deep learning-based algorithm for the detection of idiopathic full thickness macular holes in spectral domain optical coherence tomography

Abstract Background Automated identification of spectral domain optical coherence tomography (SD-OCT) features can improve retina clinic workflow efficiency as they are able to detect pathologic findings. The purpose of this study was to test a deep learning (DL)-based algorithm for the identificati...

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Bibliographic Details
Main Authors: Carolina C. S. Valentim, Anna K. Wu, Sophia Yu, Niranchana Manivannan, Qinqin Zhang, Jessica Cao, Weilin Song, Victoria Wang, Hannah Kang, Aneesha Kalur, Amogh I. Iyer, Thais Conti, Rishi P. Singh, Katherine E. Talcott
Format: Article
Language:English
Published: BMC 2024-01-01
Series:International Journal of Retina and Vitreous
Subjects:
Artificial Intelligence
Deep learning
Macular hole
Optical coherence tomography
Online Access:https://doi.org/10.1186/s40942-024-00526-8

Internet

https://doi.org/10.1186/s40942-024-00526-8

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