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Article Dans Une Revue Artificial Intelligence in Medicine Année : 2014

Using a multi-agent system approach for microaneurysm detection in fundus images

Carla Pereira
  • Fonction : Auteur
Diana Viega
  • Fonction : Auteur
Jason Mahdjoub
  • Fonction : Auteur
Luis Gonçalves
  • Fonction : Auteur
Manuel Ferreira
  • Fonction : Auteur
Joao Monteiro
  • Fonction : Auteur

Résumé

Objective Microaneurysms represent the first sign of diabetic retinopathy, and their detection is fundamental for the prevention of vision impairment. Despite several research attempts to develop an automated system to detect microaneurysms in fundus images, none has shown the level of performance required for clinical practice. We propose a new approach, based on a multi-agent system model, for microaneurysm segmentation. Methods and materials A multi-agent based approach, preceded by a preprocessing phase to allow construction of the environment in which agents are situated and interact, is presented. The proposed method is applied to two available online datasets and results are compared to other previously described approaches. Results Microaneurysm segmentation emerges from agent interaction. The final score of the proposed approach was 0.240 in the Retinopathy Online Challenge. Conclusions We achieved competitive results, primarily in detecting microaneurysms close to vessels, compared to more conventional algorithms. Despite these results not being optimum, they are encouraging and reveal that some improvements may be made.
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Dates et versions

hal-01168845 , version 1 (06-10-2022)

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Paternité - Pas d'utilisation commerciale

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Carla Pereira, Diana Viega, Jason Mahdjoub, Zahia Guessoum, Luis Gonçalves, et al.. Using a multi-agent system approach for microaneurysm detection in fundus images. Artificial Intelligence in Medicine, 2014, 60 (3), pp.179-188. ⟨10.1016/j.artmed.2013.12.005⟩. ⟨hal-01168845⟩
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