Multi-resolution retinal vessel tracker based on directional smoothing

To support ophthalmologists in their routine and enable the quantitative assessment of vascular chancres in color fundus photographs a multi-resolution approach was developed which segments the vessel tree efficiently and precisely in digital images of the retina. The algorithm starts at seed points, found in a preprocessing step and then follows the vessel, iteratively adjusting the direction of the search, and finding the center line of the vessels. As an addition, vessel branches and crossings are detected and stored in detailed lists. Every iteration of the Directional Smoothing Based (DSB) tracking process starts at a given point in the middle of a vessel. First rectangular windows for several directions in a neighborhood of this point are smoothed in the assumed direction of the vessel. The window, that results in the best contrast is then said to have the true direction of the vessel. The center point is moved into that direction 1/8th of the vessel width, and the algorithm continues with the next iteration. The vessel branch and crossing detection uses a list with unique vessel segment IDs and branch point IDs. During the tracking, when another vessel is crossed, the tracking is stopped. The newly traced vessel segment is stored in the vessel segment list, and the vessel, that had been traced before is broken up at the crossing- or branch point, and is stored as two different vessel segments. This approach has several advantages: With directional smoothing, noise is eliminated, while the edges of the vessels are kept. DSB works on high resolution images (3000 x 2000 pixel) as well as on low-resolution images (900 x 600 pixel), because a large area of the vessel is used to find the vessel direction For the detection of venous beading the vessel,;width is measured for every step of the traced vessel, With the lists of branch- and crossing points, we get a network of connected vessel segments, that can be used for further processing the retinal vessel tree.