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Automated extraction of retinal vasculature
- Source :
- Medical physics. 43(5)
- Publication Year :
- 2016
-
Abstract
- The authors propose an algorithm that automatically extracts retinal vasculature and provides a simple measure to correct the extraction. The output of the method is a network of salient points, and blood vessels are drawn by connecting the salient points using a centripetal parameterized Catmull-Rom spline.The algorithm starts by background correction. The corrected image is filtered with a bank of Gabor kernels, and the responses are consolidated to form a maximal image. After that, the maximal image is thinned to get a network of 1-pixel lines, analyzed and pruned to locate forks and form branches. Finally, the Ramer-Douglas-Peucker algorithm is used to determine salient points. When extraction is not satisfactory, the user simply shifts the salient points to edit the segmentation.On average, the authors' extractions cover 93% of ground truths (on the Drive database).By expressing retinal vasculature as a series of connected points, the proposed algorithm not only provides a means to edit segmentation but also gives knowledge of the shape of the blood vessels and their connections.
Details
- ISSN :
- 24734209
- Volume :
- 43
- Issue :
- 5
- Database :
- OpenAIRE
- Journal :
- Medical physics
- Accession number :
- edsair.pmid..........9ae75f4b4e2955cde0db0d93fefd2558