Automatic measurement of ISNT and CDR on retinal images by means of a fast and efficient method based on mathematical morphology and active contours

  1. Rafael Verdú Monedero
  2. Juan Morales Sánchez
  3. Rafael Berenguer-Vidal
  4. Inmaculada Sellés-Navarro
  5. Ana Palazón Cabanes
Libro:
From Bioinspired Systems and Biomedical Applications to Machine Learning: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019, Almería, Spain, June 3–7, 2019, Proceedings, Part II
  1. José Manuel Ferrández Vicente (dir. congr.)
  2. José Ramón Álvarez-Sánchez (dir. congr.)
  3. Félix de la Paz López (dir. congr.)
  4. Javier Toledo Moreo (dir. congr.)
  5. Hojjat Adeli (coord.)

Editorial: Springer Suiza

ISBN: 978-3-030-19651-6

Año de publicación: 2019

Páginas: 361-370

Tipo: Capítulo de Libro

DIALNET GOOGLE SCHOLAR

Resumen

This paper describes a fast and efficient method to automaticallymeasure the ISNT and CDR in retinal images. The method is basedon a robust detection of the optic disk and excavation in a enhanced retinal image by means of morphological operators. Using this coarse segmentation as initialization, two parametric active contours implemented in the frequency domain perform a fine segmentation of the optic diskand excavation. The resulting curves allow the automatic calculation of the ISNT and CDR values, which are important features to consider in the early detection of glaucoma. The accuracy and precision of the method has been tested and compared with the evaluation of two ophthalmologistsin a preliminary set of images.

Fuente de los datos: Dialnet