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 convolutional neural network (...

ver descrição completa

Detalhes bibliográficos

Principais autores:	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
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Public Library of Science (PLoS) 2019-01-01
coleção:	PLoS ONE
Acesso em linha:	https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0220063&type=printable
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!