Title: Segmentation of retinal blood vessel structure using Birnbaum-Saunders (fatigue life) probability distribution function

Authors: K. Susheel Kumar; Nagendra Pratap Singh

Addresses: Department of CSE, National Institute of Technology Hamirpur, HP-177005, India ' Department of CSE, National Institute of Technology Hamirpur, HP-177005, India

Abstract: Segmentation of retinal vessels is a prominent task. Retinal blood vessels contain essential information useful for computer-based diagnosis of various retinal pathologies, such as diabetes, hypertension, etc. Here we proposed a novel matched filter approach based on Birnbaum-Saunders PDF to improve the performance of the segmentation process of retinal blood vessels. The proposed method is divided into pre-processing, matched filter-based segmentation, and postprocessing modules. Pre-processing module used to improve the quality of input retinal image. After that, design the Birnbaum Saunders-based kernel for a matched filter by selecting suitable values of the different parameters with the help of exhaustive experimental analysis. Lastly, apply the post-processing module to find the final segmented retinal blood vessel. The proposed approach is tested on the DRIVE database only. The performance parameter such as average accuracy, F1-score, area under the curve (AUC) of the proposed approach is 94.61%, 0.684, and 0.9361, respectively.

Keywords: Birnbaum-Saunders; fatigue; probability distribution function; matched filter; retinal blood vessel segmentation; optimal thresholding-based entropy.

DOI: 10.1504/IJMEI.2022.126520

International Journal of Medical Engineering and Informatics, 2022 Vol.14 No.6, pp.484 - 500

Received: 23 Jul 2020
Accepted: 24 Dec 2020
Published online: 28 Oct 2022 *

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