A modified matched filter with double-sided thresholding for screening proliferative diabetic retinopathy

  • Authors:
  • Lei Zhang;Qin Li;Jane You;David Zhang

  • Affiliations:
  • Department of Computing, Biometric Research Center, The Hong Kong Polytechnic University, Kowloon, Hong Kong;Department of Computing, Biometric Research Center, The Hong Kong Polytechnic University, Kowloon, Hong Kong and Henan Provincial Key Laboratory on Information Networks, Zhengzhou University, Zhen ...;Department of Computing, Biometric Research Center, The Hong Kong Polytechnic University, Kowloon, Hong Kong;Department of Computing, Biometric Research Center, The Hong Kong Polytechnic University, Kowloon, Hong Kong

  • Venue:
  • IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
  • Year:
  • 2009

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Abstract

The early diagnosis of proliferative diabetic retinopathy (PDR), a common complication of diabetes that damages the retina, is crucial to the protection of the vision of diabetes sufferers. The onset of PDR is signaled by the appearance of neovascular net. Such neovascular nets might be identified using retinal vessel extraction techniques. The commonly used matched filter methods often produce false positive detections of neovascular nets due to their proneness to detect nonline edges as well as lines. In this paper, we propose a modified matched filter for retinal vessel extraction that applies a local vessel cross-section analysis using double-sided thresholding to reduce false responses to nonline edges. Our proposed modified matched filters demonstrated higher true positive rate and lesser false detection than existing matched-filter-based schemes in vessel extraction.