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Retinal Blood Vessels Extraction of Challenging Images

  • Toufique Ahmed SoomroEmail author
  • Junbin Gao
  • Zheng Lihong
  • Ahmed J. Afifi
  • Shafiullah Soomro
  • Manoranjan Paul
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 996)

Abstract

Retinal fundus examination is necessary for the early diagnosis of eye disease, especially diabetic retinopathy. Population screening often results in poor quality retinal images that complicate the automated diagnosis of retinal features, such as precise segmentation of blood vessels, microaneurysms, cotton stains, and hard exudates. Fluorescein fundus angiogram (FFA) has solved some problems, but it is invasive and has side effects. In this research work, we proposed a method of image enhancement based on contrast-sensitive steps as a valuable aid for the automatic segmentation of pathological (unhealthy) images. Experimental results based on the Digital retinal images for vessel extraction (DRIVE) and STructured analysis of the retina (STARE) databases showed that the proposed image enhancement method improved the performance over other existing methods, from 92% to 95% in accuracy and from 71% to 75% in sensitivity. This significant improvement in the contrast of retinal background images of retinal color has the potential to provide better vessel images for observing ocular diseases.

Keywords

Retinal color fundus images Enhancement method Segmentation of vessels 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Toufique Ahmed Soomro
    • 1
    Email author
  • Junbin Gao
    • 2
  • Zheng Lihong
    • 1
  • Ahmed J. Afifi
    • 3
  • Shafiullah Soomro
    • 4
  • Manoranjan Paul
    • 1
  1. 1.School of Computing and MathematicsCharles Sturt UniversityBathurstAustralia
  2. 2.The Business SchoolThe University of SydneySydneyAustralia
  3. 3.Computer Vision and Remote SensingTechnische Universität BerlinBerlinGermany
  4. 4.Department of Computer Science and EngineeringChung-Ang UniversitySeoulSouth Korea

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