Automated extraction of retinal vasculature

作者：Tan Jen Hong^*; Acharya U Rajendra; Chua Kuang Chua; Cheng Calvin; Laude Augustinus

来源：Medical Physics, 2016, 43(5): 2311-2322.

DOI：10.1118/1.4945413

• vessel extraction
• vessel segmentation
• fundus
• Gabor
• Catmull-Rom

Purpose: 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.
Methods: 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.
Results: On average, the authors' extractions cover 93% of ground truths (on the Drive database).
Conclusions: 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.

• 出版日期2016-5