Detección automatizada de microaneurismas mediante crecimiento de regiones y red neuronal Fuzzy Artmap

  1. Jiménez Carmona, Soledad
  2. Alemany Marquez, Pedro
  3. Nuñez Benjumea, Francisco
  4. Fondón, Irene
  5. Serrano Gotarredona, Carmen
  6. Acha Piñero, Begoña
  7. Failde, Inmaculada
Revista:
Archivos de la Sociedad Española de Oftalmologia

ISSN: 0365-6691

Año de publicación: 2012

Volumen: 87

Número: 9

Páginas: 284-289

Tipo: Artículo

DOI: 10.1016/J.OFTAL.2012.04.013 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Archivos de la Sociedad Española de Oftalmologia

Resumen

Objective: To assess whether the methodological changes of this new algorithm improves the results of a previously presented strategy. Methods: We enhance the image and filter out the green channel of the digital color retinography. Multitolerance thresholding was applied to obtain candidate points and make a seed growing region by varying intensities. We took 15 characteristics from each region to train a Fuzzy Artmap neural network using 42 retinal photographs. This network was then applied in the study of 11 good quality retinal photographs included in the diabetic retinopathy early detection screening program, with initial stages of retinopathy, obtained with the Topcon NW200 non-mydriatic retinal camera. Results: Two experienced ophthalmologists detected 52 microaneurysms in 11 images. The algorithm detected 39 microaneurysms and 3,752 more regions, confirming 38 microaneurysm and 135 false positives. The sensitivity is improved compared to the previous algorithm, from 60.53 to 73.08%. False positives have dropped from 41.8 to 12.27 per image. Conclusions: The new algorithm is better than the previous one, but there is still room for improvement, especially in the initial determination of seeds.