Automatic Tool for the Detection, Characterization and Intuitive Visualization of Macular Edema Regions in OCT Images

  1. Iago Otero 1
  2. Plácido L. Vidal 1
  3. Joaquim de Moura 1
  4. Jorge Novo 1
  5. 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

Año de publicación: 2019

Congreso: XoveTIC (2. 2019. A Coruña)

Tipo: Aportación congreso

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Resumen

The methodology presented in this paper aims to detect pathological regions affected by one or more of the three clinically defined types of Diabetic Macular Edema (DME). Using representative samples extracted from Optical Coherence Tomography (OCT) images, three representative classifiers are trained to analyze new input images and create an intuitive visualization of the detection results. The trained models provided a satisfactory performance for all three defined types of DME, andthe visual feedback can effectively assists clinical experts in the diagnosis of this representative and extended disease.

Fuente de los datos: Dialnet