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Machine Vision and Applications

, Volume 29, Issue 4, pp 655–666 | Cite as

Retinal vessel extraction using dynamic multi-scale matched filtering and dynamic threshold processing based on histogram fitting

  • Duoduo Gou
  • Ying Wei
  • Hong Fu
  • Ning Yan
Original Paper

Abstract

Automatic extraction of retinal vessels is of great significance in the field of medical diagnosis. Unfortunately, extracting vessels in retinal images with uneven background is a challenging task. In addition, accurate extraction of vessels with different widths is difficult. Aiming at these problems, in this paper, a new dynamic multi-scale filtering method together with a dynamic threshold processing scheme was proposed. The image is first divided into sub-images to facilitate the analysis of gray features. Then for each sub-image, the scales of the matched filter and the segmentation threshold are dynamically determined in accordance with the Gaussian fitting results of the gray distribution. Compared with the current blood vessel extraction algorithms based on multi-scale matched filter using uniform scales for the whole retinal image, the proposed method detects many fine vessels drowned by noise and avoids an overestimation of the thin vessels while improving the accuracy of segmentation in general.

Keywords

Blood vessel segmentation Multi-scale Matched filtering Gaussian fitting 

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.WAVE Joint Laboratory for Cognitive Computing TechnologyBeijingChina
  2. 2.School of Information Science and EngineeringShandong UniversityJinanChina
  3. 3.Department of Computer ScienceChu Hai College of Higher EducationTuen MunHong Kong

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