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Mean global based on hysteresis thresholding for retinal blood vessel segmentation using enhanced homomorphic filtering

  • 1214: Multimedia Medical Data-driven Decision Making
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Abstract

Retinal images are playing a very significant role in medical imaging technology. The variation in blood vessel attributes like tortuosity, focal length, branching angle, deformations like haemorrhage, lesions, etc. are good indicators of many diseases. Therefore, identifying these changes and distortions precisely can assist the ophthalmologists to detect and diagnose many diseases like diabetes, hypertension, glaucoma, stroke, etc. even in the early stage. Segmenting the vessel network is the preliminary step in the automation of the disease diagnosis process. The computerization of this segmentation process reduces the time, cost, and inconsistency due to manual segmentation. Here we present an automatic vessel segmentation technique. The proposed approach enhances the image contrast and highlights the edges using a novel cascaded pre-processing stage. In addition to this, a novel thresholding method named Mean Global Based on Hysteresis (MGBH) is introduced for segmentation. The efficiency of the suggested scheme is evaluated on the DRIVE database. The results are compared with state-of-the-art methods. The proposed method achieves better performance parameter values. The advantages of the proposed method include fast processing and high segmentation accuracy with simplified implementation. Moreover, this work can be extended to segment noisy and diseased fundus images.

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Authors and Affiliations

  1. Department of Electronics and Telecommunication Engineering, VSSUT, Burla, 768018, India

    Sakambhari Mahapatra & U. R. Jena

  2. Department of Computer Science and Engineering, Chandigarh University, Mohali, 140413, India

    Sonali Dash

Authors
  1. Sakambhari Mahapatra
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  2. U. R. Jena
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  3. Sonali Dash
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Correspondence to Sakambhari Mahapatra.

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Mahapatra, S., Jena, U.R. & Dash, S. Mean global based on hysteresis thresholding for retinal blood vessel segmentation using enhanced homomorphic filtering. Multimed Tools Appl 81, 41911–41928 (2022). https://doi.org/10.1007/s11042-022-13517-4

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  • DOI: https://doi.org/10.1007/s11042-022-13517-4

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