4.2 Article

An Effective Retinal Blood Vessel Segmentation by Using Automatic Random Walks Based on Centerline Extraction

Journal

BIOMED RESEARCH INTERNATIONAL
Volume 2020, Issue -, Pages -

Publisher

HINDAWI LTD
DOI: 10.1155/2020/7352129

Keywords

-

Funding

  1. National Natural Science Foundation of China [81101110]
  2. Natural Science Foundation of Fujian Province [2019J01272, 2018H0027, 2019H0040]
  3. program for Changjiang Scholars and Innovative Research Team in University [IRT_15R10]
  4. Special Funds of the Central Government Guiding Local Science and Technology Development [2017L3009]
  5. Youth program of Fujian Education Department [JAT170620]

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The retinal blood vessel analysis has been widely used in the diagnoses of diseases by ophthalmologists. According to the complex morphological characteristics of the blood vessels in normal and abnormal images, an automatic method by using the random walk algorithms based on the centerlines is proposed to segment retinal blood vessels. Hessian-based multiscale vascular enhancement filtering is used to display the vessel structures in maximum intensity projection. Random walk algorithm provides a unique and quality solution, which is robust to weak object boundaries. Seed groups in the random walk segmentation are labeled according to the centerlines, which are extracted by using the divergence of the normalized gradient vector field and the morphological method. Experiments of the proposed method are implemented on the publicly available STARE (the Structured Analysis of the Retina) database. The results are compared to other existing retinal blood vessel segmentation methods with respect to the accuracy, sensitivity, and specificity, and the proposed method is proved to be more sensitive in detecting the retinal blood vessels in both normal and pathological areas.

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