Automatic Blood Vessel Extraction of Fundus Images Employing Fuzzy Approach

Authors

Charu Bhardwaj
Jaypee Univeristy of Information Technology, Solan, India
Shruti Jain
Jaypee Univeristy of Information Technology, Solan, India
Meenakshi Sood
Jaypee Univeristy of Information Technology, Solan, India
DOI: https://doi.org/10.52549/ijeei.v7i4.991
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Published: 20-11-2019 • Issue: Vol. 7 No. 4: December 2019 • Section: Computer_&_Informatics

Abstract

Diabetic Retinopathy is a retinal vascular disease that is characterized by progressive deterioration of blood vessels in the retina and is distinguished by the appearance of different types of clinical lesions like microaneurysms, hemorrhages, exudates etc. Automated detection of the lesions plays significant role for early diagnosis by enabling medication for the treatment of severe eye diseases preventing visual loss. Extraction of blood vessels can facilitate ophthalmic services by automating computer aided screening of fundus images. This paper presents blood vessel extraction algorithms with ensemble of pre-processing and post-processing steps which enhance the image quality for better analysis of retinal images for automated detection. Extensive performance based evaluation of the proposed approaches is done over four databases on the basis of statistical parameters. Comparison of both blood vessel extraction techniques on different databases reveals that fuzzy based approach gives better results as compared to Kirsch’s based algorithm. The results obtained from this study reveal that 89% average accuracy is offered by the proposed MBVEKA and 98% for proposed BVEFA.

Keywords: Blood Vessel Extraction; Diabetic Retinopathy; Exudates; Fuzzy; Hemorrhages; Kirsch’s Algorithm

Author Biographies

Charu Bhardwaj
Charu Bhardwaj is a Ph.D. Research Scholar and teaching assistant in the Department of Electronics and Communication Engineering, JUIT Waknaghat, Solan. Her research area is Digital Signal Processing, Digital Image Processing and Biomedical Image Processing. The Author has published articles in 4th IEEE Conference on “Computing for Sustainable Global Development" (INDIACOM 2017) and Journal of Global Pharma Technology. As a Research Associate she is currently working in JUIT and giving her constant efforts to make the research work a success.
Shruti Jain
Shruti Jain has received PhD degree from Jaypee University of Information Technology, Waknaghat, Solan. She has a teaching experience of around 13 years and before joining JUIT, she worked as Assistant Professor in Haryana Engineering College, Jagadhari, Ambala College of Engineering, Ambala. She has specialization in Biomedical Signal Processing, Computer- Aided design of FPGA and VLSI circuits, combinatorial optimization. She has published more than 50 papers in reputed journals and 30 papers in International conferences.  She is a senior member of IEEE, life member of Biomedical Engineering Society of India and member of IAENG. She is currently working as Associate Professor in the Department of Electronics and Communication Engineering, JUIT Waknaghat.
Meenakshi Sood

Meenakshi Sood is Senior Assistant Professor in the Department of Electronics and Communication Engineering at Jaypee University of Information Technology, Waknaghat, H.P, India and received her Ph.D in Biomedical Signal Processing. She is Gold Medalist and has been awarded Academic Award for her performance in Master of Engineering (Hons.) from Panjab Univeristy, Chandigarh. Her research areas interests are Image and Signal processing, Antenna Design, Metamaterials and Soft Computing. She has published more than 25 papers in reputed journals and 30 papers in International conferences.  She is a senior member of IEEE and giving her continuous guidance and efforts as Department Coordinator at JUIT. She has published course material of "Digital Electronics and Microprocessors " for ICDOEL , H.P University. She had been selected as GSE member of Rotary International and visited USA in Exchange Program.

How to Cite

[1]
C. Bhardwaj, S. Jain, and M. Sood, “Automatic Blood Vessel Extraction of Fundus Images Employing Fuzzy Approach”, IJEEI, vol. 7, no. 4, pp. 757–771, Nov. 2019, doi: 10.52549/ijeei.v7i4.991.