Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images

Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images

Evaluating the discrimination ability of a deep convolution neural network for ultrawide-field pseudocolor imaging and ultrawide-field autofluorescence of retinitis pigmentosa. In total, the 373 ultrawide-field pseudocolor and ultrawide-field autofluorescence images (150, retinitis pigmentosa; 223,...

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Bibliographic Details
Main Authors: Hiroki Masumoto, Hitoshi Tabuchi, Shunsuke Nakakura, Hideharu Ohsugi, Hiroki Enno, Naofumi Ishitobi, Eiko Ohsugi, Yoshinori Mitamura
Format: Article
Language:English
Published: PeerJ Inc. 2019-05-01
Series:PeerJ
Subjects:
Neural network
Retinitis pigmentosa
Screening system
Ultrawide-filed pseudocolor imaging
Ultrawide-field autofluorescence
Online Access:https://peerj.com/articles/6900.pdf

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https://peerj.com/articles/6900.pdf

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