Name
Abstract | ||
|---|---|---|
Retinal images contain forests of mutually intersecting and overlapping venous and arterial vascular trees. The geometry of these trees shows adaptation to vascular diseases including diabetes, stroke and hypertension. Segmentation of the retinal vascular network is complicated by inconsistent vessel contrast, fuzzy edges, variable image quality, media opacities, complex intersections and overlaps. This paper presents a Bayesian approach to resolving the configuration of vascular junctions to correctly construct the vascular trees. A probabilistic model of vascular joints (terminals, bridges and bifurcations) and their configuration in junctions is built, and Maximum A Posteriori (MAP) estimation used to select most likely configurations. The model is built using a reference set of 3010 joints extracted from the DRIVE public domain vascular segmentation dataset, and evaluated on 3435 joints from the DRIVE test set, demonstrating an accuracy of 95.2%. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CVPR.2014.397 | Computer Vision and Pattern Recognition |
Keywords | Field | DocType |
Bayes methods,blood vessels,diseases,eye,fuzzy set theory,image segmentation,maximum likelihood estimation,medical image processing,trees (mathematics),Bayesian approach,Bayesian framework,DRIVE public domain vascular segmentation dataset,MAP estimation,arterial vascular trees,complex intersections,diabetes,fuzzy edges,hypertension,local configuration,maximum a posteriori estimation,media opacities,mutually intersecting venous,mutually overlapping venous,probabilistic model,retinal images,retinal junctions,retinal vascular network segmentation,stroke,variable image quality,vascular diseases,vascular junction configuration,vessel contrast,Retinal vessels configuration,junction resolution,vessels connectivity,vessels trees reconstruction | Computer vision,Pattern recognition,Computer science,Segmentation,Fuzzy logic,Image quality,Artificial intelligence,Statistical model,Retinal,Maximum a posteriori estimation,Bayesian probability,Test set | Conference |
ISSN | Citations | PageRank |
1063-6919 | 2 | 0.39 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Touseef Ahmad Qureshi | 1 | 10 | 1.60 |
| Andrew Hunter | 2 | 140 | 9.10 |
| Bashir Al-diri | 3 | 41 | 7.50 |