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Proceedings Paper

Ridge-branch-based blood vessel detection algorithm for multimodal retinal images
Author(s): Y. Li; N. Hutchings; R. W. Knighton; G. Gregori; Brandon J. Lujan; J. G. Flanagan
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Paper Abstract

Automatic detection of retinal blood vessels is important to medical diagnoses and imaging. With the development of imaging technologies, various modals of retinal images are available. Few of currently published algorithms are applied to multimodal retinal images. Besides, the performance of algorithms with pathologies is expected to be improved. The purpose of this paper is to propose an automatic Ridge-Branch-Based (RBB) detection algorithm of blood vessel centerlines and blood vessels for multimodal retinal images (color fundus photographs, fluorescein angiograms, fundus autofluorescence images, SLO fundus images and OCT fundus images, for example). Ridges, which can be considered as centerlines of vessel-like patterns, are first extracted. The method uses the connective branching information of image ridges: if ridge pixels are connected, they are more likely to be in the same class, vessel ridge pixels or non-vessel ridge pixels. Thanks to the good distinguishing ability of the designed "Segment-Based Ridge Features", the classifier and its parameters can be easily adapted to multimodal retinal images without ground truth training. We present thorough experimental results on SLO images, color fundus photograph database and other multimodal retinal images, as well as comparison between other published algorithms. Results showed that the RBB algorithm achieved a good performance.

Paper Details

Date Published: 27 March 2009
PDF: 12 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72594K (27 March 2009); doi: 10.1117/12.812414
Show Author Affiliations
Y. Li, Univ. of Miami Miller School of Medicine (United States)
N. Hutchings, Univ. of Waterloo (Canada)
R. W. Knighton, Univ. of Miami Miller School of Medicine (United States)
G. Gregori, Univ. of Miami Miller School of Medicine (United States)
Brandon J. Lujan, Univ. of California, Berkeley (United States)
J. G. Flanagan, Univ. of Waterloo (Canada)
Univ. of Toronto (Canada)


Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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