Title: Segmentation of retinal blood vessels by using a matched filter based on second derivative of Gaussian

Authors: Nagendra Pratap Singh; Rajeev Srivastava

Addresses: Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi 221005, India ' Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi 221005, India

Abstract: An accurate retinal blood vessel segmentation is a prominent task in computer aided diagnosis of various retinal pathology such as hypertension, diabetes, glaucoma, etc. The matched filter based retinal blood vessel segmentation approaches are simple yet effective. However, matched filter based approach detect both vessels and non-vessel edges. Hence, this also leads to false vessels i.e. non-vessels detection. To overcome the problem of detecting the non-vessel edges, here we propose an extension of matched filter based on the second derivative of Gaussian (SDOG-MF). The proposed approach is simple and effective for the segmentation of thin as well as thick retinal blood vessels. The experimental results obtained for both DRIVE and STARE databases confirms that the proposed method has higher TPR, FPR, and accuracy as compared with other available retinal blood vessel segmentation approaches in literature. Further, the performance of the proposed method is also better for the segmentation of pathological retinal images.

Keywords: matched filters; retinal blood vessels; image segmentation; local entropy thresholding; computer aided diagnosis; retinal pathology; hypertension; diabetes; glaucoma; retinal images; medical images.

DOI: 10.1504/IJBET.2016.078286

International Journal of Biomedical Engineering and Technology, 2016 Vol.21 No.3, pp.229 - 246

Received: 20 Aug 2015
Accepted: 03 Nov 2015
Published online: 14 Aug 2016 *

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