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3D deep convolutional neural network for predicting neurosensory retinal thickness map from spectral domain optical coherence tomography volumes
Author(s): Oscar J. Perdomo; Hernan A. Rios; Francisco J. Rodríguez; Fabio A. González
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Paper Abstract

Age-related macular degeneration is a common cause of vision loss in people aging 55 and older. The condition affects the light-sensing cells in the macula limiting the sharp and central vision. On the other hand, Spectral Domain Optical Coherence Tomography (SD-OCT) allow highlighting abnormalities and thickness in the retinal layers which are useful for age-related macular degeneration diagnosis and follow up. The Neurosensory retina (NSR) map is defined as the thickness between the inner limiting membrane layer and the inner aspect of the retinal pigment epithelium complex. Additionally, the NSR map has been used to differentiate between healthy and subjects with macular problems, but the plotting of the retinal thickness map depends critically on additional manufacturer interpretation software to automatically drawing. Therefore, this paper presents an end-to-end 3D convolutional neural network to automatically extract nine thickness mean values to draw the NSR map from an SD-OCT.

Paper Details

Date Published: 21 December 2018
PDF: 6 pages
Proc. SPIE 10975, 14th International Symposium on Medical Information Processing and Analysis, 109750I (21 December 2018); doi: 10.1117/12.2511597
Show Author Affiliations
Oscar J. Perdomo, Univ. Nacional de Colombia (Colombia)
Hernan A. Rios, Fundación Oftalmológica Nacional (Colombia)
Francisco J. Rodríguez, Fundación Oftalmológica Nacional (Colombia)
Fabio A. González, Univ. Nacional de Colombia (Colombia)


Published in SPIE Proceedings Vol. 10975:
14th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva, Editor(s)

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