3D deep convolutional neural network for predicting neurosensory retinal thickness map from spectral domain optical coherence tomography volumes

Oscar J. Perdomo, Hernan A. Rios, Francisco J. Rodríguez, Fabio A. González

Resultado de la investigación: Capítulo en Libro/Reporte/ConferenciaContribución a la conferencia

1 Cita (Scopus)

Resumen

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.

Idioma originalInglés estadounidense
Título de la publicación alojada14th International Symposium on Medical Information Processing and Analysis
EditoresNatasha Lepore, Eduardo Romero, Jorge Brieva
EditorialSPIE
ISBN (versión digital)9781510626058
DOI
EstadoPublicada - 2018
Publicado de forma externa
Evento14th International Symposium on Medical Information Processing and Analysis, SIPAIM 2018 - Mazatlan, México
Duración: oct 24 2018oct 26 2018

Serie de la publicación

NombreProceedings of SPIE - The International Society for Optical Engineering
Volumen10975
ISSN (versión impresa)0277-786X
ISSN (versión digital)1996-756X

Conferencia

Conferencia14th International Symposium on Medical Information Processing and Analysis, SIPAIM 2018
País/TerritorioMéxico
CiudadMazatlan
Período10/24/1810/26/18

All Science Journal Classification (ASJC) codes

  • Materiales electrónicos, ópticos y magnéticos
  • Física de la materia condensada
  • Informática aplicada
  • Matemáticas aplicadas
  • Ingeniería eléctrica y electrónica

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