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A Fusion Based Approach for Blood Vessel Segmentation from Fundus Images by Separating Brighter Optic Disc

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Abstract—

In ophthalmology, blood vessel segmentation from fundus images plays a significant role in automated retinal disease screening systems. Several research papers on blood vessel segmentation suggest enhancing fundus images before segmentation significantly to improve performance. The brightness of the optic disc region in a fundus image negatively influences the enhancement of relatively darker vessel pixels. Segregation of brighter optic disc from fundus images before its enhancement is the fundamental idea behind developing the proposed framework. Initially, the optic disc is extracted from the input fundus image to form two images, one containing optical disc and the other, fundus image without optical disk. In the second stage, both the images are enhanced independently, followed by blood vessel segmentation. Finally, the segmented blood vessels from the images are fused to obtain a single image. Experiments conducted with fundus images from DRIVE, STARE, and CHASE_DB1 databases show improvement in the identification of blood vessel pixels.

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Authors and Affiliations

  1. Department of Information Technology, Kannur University, 670567, Kannur, Kerala, India

    Farha Fatina Wahid & K. Sugandhi

  2. Department of Computer Science and Engineering, Christ (Deemed to Be University), Kengeri Campus, 560074, Bengaluru, India

    G. Raju

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  1. Farha Fatina Wahid
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Correspondence to Farha Fatina Wahid, K. Sugandhi or G. Raju.

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This article is a completely original work of its authors; it has not been published before and will not be sent to other publications until the PRIA Editorial Board decides not to accept it for publication.

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The process of writing and the content of the article does not give grounds for raising the issue of a conflict of interest.

Additional information

Farha Fatina Wahid Received a Master’s in Computer Application and PhD in Computer Science from Kannur University, Kerala, India. Her research interests are in medical image processing, high-performance computing, and machine learning.

K. Sugandhi received a Master’s in Computer Science from the Central University of Kerala (2013), MPhil (2014), and PhD in Computer Science (2021) from the Kannur University, Kerala, India. Her research interests are in image and video processing, machine learning, and high-performance computing.

Dr. G. Raju is currently working in the Department of Computer Science and Engineering, Christ (Deemed to Be University), Bengaluru. He obtained his Master’s and Doctoral degrees from the University of Kerala, India. His area of research includes Image Processing, Computer Vision, Machine Learning, and Data Science. He has 29 years of teaching and 20 years of research experience. He has more than 100 publications to his credit and guided 22 PhD Scholars.

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Wahid, F.F., Sugandhi, K. & Raju, G. A Fusion Based Approach for Blood Vessel Segmentation from Fundus Images by Separating Brighter Optic Disc. Pattern Recognit. Image Anal. 31, 811–820 (2021). https://doi.org/10.1134/S105466182104026X

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