Name
Title | ||
|---|---|---|
Particle Swarm Optimization Approach For The Segmentation Of Retinal Vessels From Fundus Images |
Abstract | ||
|---|---|---|
In this paper, we propose to use the Particle Swarm Optimization (PSO) algorithm to improve the Multi-Scale Line Detection (MSLD) method for the retinal blood vessel segmentation problem. The PSO algorithm is applied to find the best arrangement of scales in the basic line detector method. The segmentation performance was validated using a public high-resolution fundus images database containing healthy subjects. The optimized MSLD method demonstrates fast convergence to the optimal solution reducing the execution time by approximately 35%. For the same level of specificity, the proposed approach improves the sensitivity rate by 3.1% compared to the original MSLD method. The proposed method will allow to reduce the amount of missing vessels segments that might lead to false positives of red lesions detection in CAD systems used for diabetic retinopathy diagnosis. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-59876-5_61 | IMAGE ANALYSIS AND RECOGNITION, ICIAR 2017 |
Keywords | Field | DocType |
Retinal blood vessel segmentation, Optimization, Particle Swarm Optimization Algorithm, Multi-scale Line Detection | Convergence (routing),Particle swarm optimization,Computer vision,Pattern recognition,Computer science,Segmentation,Fundus (eye),Artificial intelligence,Execution time,Retinal,Detector,False positive paradox | Conference |
Volume | ISSN | Citations |
10317 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 14 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bilal Khomri | 1 | 0 | 0.34 |
| Argyrios Christodoulidis | 2 | 0 | 0.34 |
| Leila Djerou | 3 | 0 | 0.34 |
| Mohamed Chaouki Babahenini | 4 | 9 | 3.87 |
| Farida Cheriet | 5 | 482 | 61.48 |