Intraretinal Fluid Detection by Means of a Densely Connected Convolutional Neural Network Using Optical Coherence Tomography Images

  1. Plácido L. Vidal
  2. Joaquim de Moura 1
  3. Jorge Novo 1
  4. Marcos Ortega 1
  1. 1 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

Libro:
XoveTIC 2019: The 2nd XoveTIC Conference (XoveTIC 2019), A Coruña, Spain, 5–6 September
  1. Alberto Alvarellos González (ed. lit.)
  2. José Joaquim de Moura Ramos (ed. lit.)
  3. Beatriz Botana Barreiro (ed. lit.)
  4. Javier Pereira Loureiro (ed. lit.)
  5. Manuel F. González Penedo (ed. lit.)

Editorial: MDPI

ISBN: 978-3-03921-444-0,  978-3-03921-443-3

Ano de publicación: 2019

Congreso: XoveTIC (2. 2019. A Coruña)

Tipo: Achega congreso

DIALNET GOOGLE SCHOLAR lock_openAcceso aberto editor

Resumo

Hereby we present a methodology with the objective of detecting retinal fluid accumulations in between the retinal layers. The methodology uses a robust Densely Connected Neural Network to classify thousands of subsamples, extracted from a given Optical Coherence Tomography image. Posteriorly, using the detected regions, it satisfactorily generates a coherent and intuitive confidence map by means of a voting strategy.

Fonte de datos: Dialnet