Name
Abstract | ||
|---|---|---|
Retinal vessels play an important role in the diagnostic procedure of retinopathy. Accurate segmentation of retinal vessels is crucial for pathological analysis. In this paper, we propose a new retinal vessel segmentation method based on level set and region growing. Firstly, a retinal vessel image is preprocessed by the contrast-limited adaptive histogram equalization and a 2D Gabor wavelet to enhance the vessels. Then, an anisotropic diffusion filter is used to smooth the image and preserve vessel boundaries. Finally, the region growing method and a region-based active contour model with level set implementation are applied to extract retinal vessels, and their results are combined to achieve the final segmentation. Comparisons are conducted on the publicly available DRIVE and STARE databases using three different measurements. Experimental results show that the proposed method reaches an average accuracy of 94.77% on the DRIVE database and 95.09% on the STARE database. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.patcog.2014.01.006 | Pattern Recognition |
Keywords | Field | DocType |
Retinal vessel segmentation,2D Gabor wavelet,Level set,Region growing | Active contour model,Computer vision,Scale-space segmentation,Pattern recognition,Segmentation,Gabor wavelet,Level set,Adaptive histogram equalization,Artificial intelligence,Region growing,Retinal,Mathematics | Journal |
Volume | Issue | ISSN |
47 | 7 | 0031-3203 |
Citations | PageRank | References |
48 | 1.19 | 25 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu-Qian Zhao | 1 | 92 | 9.98 |
| Xiao-Hong Wang | 2 | 48 | 1.19 |
| Xiao-Fang Wang | 3 | 52 | 1.62 |
| Frank Y. Shih | 4 | 1103 | 89.56 |