Segmentation of Retinal Blood Vessels Based on Cake Filter.

Segmentation of retinal blood vessels is significant to diagnosis and evaluation of ocular diseases like glaucoma and systemic diseases such as diabetes and hypertension. The retinal blood vessel segmentation for small and low contrast vessels is still a challenging problem. To solve this problem, a...

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Publicado en:BioMed Research International Vol. 2015; pp. 1 - 12
Autores principales: Bao, Xi-Rong, Ge, Xin, She, Li-Huang, Zhang, Shi
Formato: diagnostic images research tables/charts Journal Article
Publicado: Wiley-Blackwell 11/9/2015
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 11/9/2015
      vid: 2015
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2015/137024
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        atl: Segmentation of Retinal Blood Vessels Based on Cake Filter.
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        au:
          Bao, Xi-Rong
          Ge, Xin
          She, Li-Huang
          Zhang, Shi
        affil: School of Information Science and Engineering Northeastern University, Shenyang, Liaoning 110819, China
      sug:
        subj:
          Blood Vessels
          Retina Anatomy and Histology
          Hypertension Diagnosis
          Diabetes Mellitus Diagnosis
      ab: Segmentation of retinal blood vessels is significant to diagnosis and evaluation of ocular diseases like glaucoma and systemic diseases such as diabetes and hypertension. The retinal blood vessel segmentation for small and low contrast vessels is still a challenging problem. To solve this problem, a new method based on cake filter is proposed. Firstly, a quadrature filter band called cake filter band is made up in Fourier field. Then the real component fusion is used to separate the blood vessel from the background. Finally, the blood vessel network is got by a self-adaption threshold. The experiments implemented on the STARE database indicate that the new method has a better performance than the traditional ones on the small vessels extraction, average accuracy rate, and true and false positive rate.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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