کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6920951 | 864480 | 2016 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Blood vessel extraction and optic disc removal using curvelet transform and kernel fuzzy c-means
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Blood vessel extraction and optic disc removal using curvelet transform and kernel fuzzy c-means Blood vessel extraction and optic disc removal using curvelet transform and kernel fuzzy c-means](/preview/png/6920951.png)
چکیده انگلیسی
This paper proposes an automatic blood vessel extraction method on retinal images using matched filtering in an integrated system design platform that involves curvelet transform and kernel based fuzzy c-means. Since curvelet transform represents the lines, the edges and the curvatures very well and in compact form (by less number of coefficients) compared to other multi-resolution techniques, this paper uses curvelet transform for enhancement of the retinal vasculature. Matched filtering is then used to intensify the blood vessels' response which is further employed by kernel based fuzzy c-means algorithm that extracts the vessel silhouette from the background through non-linear mapping. For pathological images, in addition to matched filtering, Laplacian of Gaussian filter is also employed to distinguish the step and the ramp like signal from that of vessel structure. To test the efficacy of the proposed method, the algorithm has also been applied to images in presence of additive white Gaussian noise where the curvelet transform has been used for image denoising. Performance is evaluated on publicly available DRIVE, STARE and DIARETDB1 databases and is compared with the large number of existing blood vessel extraction methodologies. Simulation results demonstrate that the proposed method is very much efficient in detecting the long and the thick as well as the short and the thin vessels with an average accuracy of 96.16% for the DRIVE and 97.35% for the STARE database wherein the existing methods fail to extract the tiny and the thin vessels.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 70, 1 March 2016, Pages 174-189
Journal: Computers in Biology and Medicine - Volume 70, 1 March 2016, Pages 174-189
نویسندگان
Sudeshna Sil Kar, Santi P. Maity,