Junction Resolution Projects

These project aim to form a retinal vascular graph from segmented retinal vessels, by determining the branching pattern of retinal arteries and veins. These projects are the first extensive study of an algorithm to resolve the geometry of retinal junctions, and to build a retinal graph, from vessel segments.

We have conducted our analysis using digital fundal images from diabetic screening populations. However, the algorithms exploit geometrical features of vessels that are not highly dependent on the imaging modality, although excessive sensor noise might affect performance. We expect that the techniques will be suitable for fluorescent angiography and other image capture techniques, although verifying this supposition remains for future work.


The public-domain DRIVE database was used to evaluate the algorithms. The blood vessels of the DRIVE test set were segmented using the ESP algorithm. Click here to download these segments.

Each segment is represented by a set of profiles. Each profile consists of two edge points. The distance between these points represents the width of the profile while the perpendicular vector to the line segment joining them represents the vessel profile direction.

The resulting system is able to determine the connectivity of most junctions in the retinal graph. Overlapping segments cause specific problems, and are identified by their unusual configuration and processed separately.


Currently we are developing automated methods to extract measurements from the identified junctions, and evaluate the predictive and diagnostic potential of these for a variety of retinal diseases.

Also, a bayesian framework for the local configuration of retinal junctions is under development and as a part of this project a new dataset fro bifurcations based on the DRIVE dataset will be extracted.


The Drive Segment-Junction Set is under construction.


The output of this project were published in a paper entitled ”Automated analysis of retinal vascular network connectivity.” The abstract is given below:

This paper describes an algorithm that forms a retinal vessel graph by analysing the potential connectivity of segmented retinal vessels. Self organizing feature maps (SOFMs) are used to model implicit cost functions for the junction geometry. The algorithm uses these cost functions to resolve the configuration of local sets of segment ends, thus determining the network connectivity. The system includes specialized algorithms to handle overlapping vessels. The algorithm is tested on junctions drawn from the public-domain DRIVE database.


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Dr. Bashir Al-Diri (PhD., MSc., BSc., FHEA)
Lincoln School of Computer Science
University of Lincoln
Brayford Pool
Lincoln LN6 7TS
United Kingdom
Email My Webpage Phone: +44 1522 837111
Fax: +44 1522 886974