Share Email Print

Proceedings Paper

Multiresolution retinal vessel tracker based on directional smoothing
Author(s): Karl-Hans Englmeier; Simon Bichler; K. Schmid; M. Maurino; Massimo Porta; Toke Bek; B. Ege; Ole Vilhelm Larsen; Ok Hejlesen
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

To support ophthalmologists in their routine and enable the quantitative assessment of vascular changes 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.

Paper Details

Date Published: 24 April 2002
PDF: 8 pages
Proc. SPIE 4683, Medical Imaging 2002: Physiology and Function from Multidimensional Images, (24 April 2002); doi: 10.1117/12.463587
Show Author Affiliations
Karl-Hans Englmeier, Forschungszentrum fuer Umwalt und Gesundheit (Germany)
Simon Bichler, Forschungszentrum fuer Umwalt und Gesundheit (Germany)
K. Schmid, Forschungszentrum fuer Umwalt und Gesundheit (Germany)
M. Maurino, Univ. of Turin (Italy)
Massimo Porta, Univ. of Turin (Italy)
Toke Bek, Aarhus Univ. Hospital (Denmark)
B. Ege, Aalborg Univ. (Denmark)
Ole Vilhelm Larsen, Aalborg Univ. (Denmark)
Ok Hejlesen, Aalborg Univ. (Denmark)

Published in SPIE Proceedings Vol. 4683:
Medical Imaging 2002: Physiology and Function from Multidimensional Images
Anne V. Clough; Chin-Tu Chen, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?