Validation of automated artificial intelligence segmentation of optical coherence tomography images.

Validation of automated artificial intelligence segmentation of optical coherence tomography images.

<h4>Purpose</h4>To benchmark the human and machine performance of spectral-domain (SD) and swept-source (SS) optical coherence tomography (OCT) image segmentation, i.e., pixel-wise classification, for the compartments vitreous, retina, choroid, sclera.<h4>Methods</h4>A convol...

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Bibliographic Details
Main Authors: Peter M Maloca, Aaron Y Lee, Emanuel R de Carvalho, Mali Okada, Katrin Fasler, Irene Leung, Beat Hörmann, Pascal Kaiser, Susanne Suter, Pascal W Hasler, Javier Zarranz-Ventura, Catherine Egan, Tjebo F C Heeren, Konstantinos Balaskas, Adnan Tufail, Hendrik P N Scholl
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0220063

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https://doi.org/10.1371/journal.pone.0220063

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