Authors:
Carla Pereira
1
;
Jason Mahdjoub
2
;
Zahia Guessoum
2
;
Luis Gonçalves
3
and
Manuel Ferreira
1
Affiliations:
1
University of Minho, Portugal
;
2
University of Reims, France
;
3
Centro Hospitalar do Alto Ave, Guimarães and SA., Portugal
Keyword(s):
Diabetic Retinopathy, Fundus Image Analyzing, Blood Vessels Segmentation, Multi-Agents System.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
Abstract:
Retinal blood vessels segmentation by color fundus images analysis has got huge importance for the diabetic retinopathy early diagnosis. Several interesting computational approaches have been done in this field, but none of them has shown the required performance due to the use of global approaches. Therefore, a new approach is proposed based on an organization of agents enabling vessels detection. This multi-agent approach is preceded by a preprocessing phase in which the fundamental filter is a Kirsch derivative improved version. This first phase allows an environment construction where the agents are situated and interact. Then, blood vessels segmentation emerges from agents’ interaction. According to this study, competitive results were achieved comparing to those found in the present literature. It seems to be that a very efficient system for the diabetic retinopathy diagnosis can be built using MAS mechanisms.