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  • 标题:A Novel Threshold based Method for Vessel Intensity Detection and Extraction from Retinal Images
  • 本地全文:下载
  • 作者:Farha Fatina Wahid ; Sugandhi K ; Raju G
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2021
  • 卷号:12
  • 期号:6
  • 页码:546
  • DOI:10.14569/IJACSA.2021.0120663
  • 出版社:Science and Information Society (SAI)
  • 摘要:Retinal vessel segmentation is an active research area in medical image processing. Several research outcomes on retinal vessel segmentation have emerged in recent years. Each method has its own pros and cons, either in the vessel detection stage or in its extraction. Based on a detailed empirical investigation, a novel retinal vessel extraction architecture is proposed, which makes use of a couple of existing algorithms. In the proposed algorithm, vessel detection is carried out using a cumulative distribution function-based thresholding scheme. The resultant vessel intensities are extracted based on the hysteresis thresholding scheme. Experiments are carried out with retinal images from DRIVE and STARE databases. The results in terms of Sensitivity, Specificity, and Accuracy are compared with five standard methods. The proposed method outperforms all methods in terms of Sensitivity and Accuracy for the DRIVE data set, whereas for STARE, the performance is comparable with the best method.
  • 关键词:Retinal images; blood vessel detection; and segmentation; segmentation; hysteresis thresholding; cumulative distribution function introduction
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