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

Research output: Contribution to journalArticlespeer-review

4 Citations (Scopus)

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. Copyright © 2018 Springer-Verlag GmbH Germany, part of Springer Nature.
Original languageEnglish
Pages (from-to)655-666
JournalMachine Vision and Applications
Volume29
Issue number4
Early online date03 Apr 2018
DOIs
Publication statusPublished - May 2018

Citation

Gou, D., Wei, Y., Fu, H., & Yan, N. (2018). Retinal vessel extraction using dynamic multi-scale matched filtering and dynamic threshold processing based on histogram fitting. Machine Vision and Applications, 29(4), 655-666. doi: 10.1007/s00138-018-0924-0

Keywords

  • Blood vessel segmentation
  • Multi-scale
  • Matched filtering
  • Gaussian fitting

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