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

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 prop...

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Publicado en:BioMed Research International pp. 1 - 12
Autores principales: Gao, Jianqing, Chen, Guannan, Lin, Wenru
Formato: diagnostic images equations & formulas pictorial research Journal Article
Publicado: Wiley-Blackwell 3/24/2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 3/24/2020
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2020/7352129
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        atl: An Effective Retinal Blood Vessel Segmentation by Using Automatic Random Walks Based on Centerline Extraction.
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        au:
          Gao, Jianqing
          Chen, Guannan
          Lin, Wenru
        affil: Smart Home Information Collection and Processing on Internet of Things Laboratory of Digital Fujian, Fujian Jiangxia University, Fuzhou 350108, China
      sug:
        subj:
          Retina Blood Supply
          Blood Vessels Anatomy and Histology
          Diagnostic Imaging Methods
          Image Processing, Computer Assisted
          Image Enhancement
          Algorithms
          Sensitivity and Specificity
      ab: 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.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        pictorial
        research
        Journal Article
      ougenre: Article
    language: English
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