Department of Computer Science
Retinal blood vessels segmentation using the radial projection and supervised classification
The low-contrast and narrow blood vessels in retinal images are difficult to be extracted but useful in revealing certain systemic disease. Motivated by the goals of improving detection of such vessels, we propose the radial projection method to locate the vessel centerlines. Then the supervised classification is used for extracting the major structures of vessels. The final segmentation is obtained by the union of the two types of vessels after removal schemes. Our approach is tested on the STARE database, the results demonstrate that our algorithm can yield better segmentation. © 2010 Crown Copyright.
Source Publication Title
Proceedings: 2010 20th International Conference on Pattern Recognition
Peng, Qinmu, Xinge You, Long Zhou, and Yiu-Ming Cheung. "Retinal blood vessels segmentation using the radial projection and supervised classification." Proceedings: 2010 20th International Conference on Pattern Recognition (2010): 1489-1492.