Hierarchical local binary pattern for branch retinal vein occlusion recognition with fluorescein angiography images

Hui ZHANG, Zenghai CHEN, Zheru CHI, Hong FU

Research output: Contribution to journalArticlespeer-review

4 Citations (Scopus)

Abstract

Branch retinal vein occlusion (BRVO) is one of the most common retinal diseases. Without timely diagnosis and treatment, it would seriously impair the patient's vision. Automatic recognition of BRVO could significantly improve the efficiency of diagnosis. A feature representation method is proposed for the automatic recognition of BRVO with fluorescein angiography (FA) images. The proposed feature representation method, termed hierarchical local binary pattern (HLBP), is comprised of LBPs in a hierarchical fashion with max‐pooling. A FA image dataset is established to evaluate the performance of the HLBP method. Experimental results demonstrate the superior performance of the proposed HLBP method for BRVO recognition with FA images, by comparing it with state‐of‐the‐art methods. Copyright © 2014 The Institution of Engineering and Technology.
Original languageEnglish
Pages (from-to)1902-1904
JournalElectronics Letters
Volume50
Issue number25
Early online date01 Dec 2014
DOIs
Publication statusPublished - Dec 2014

Citation

Zhang, H., Chen, Z., Chi, Z., & Fu, H. (2014). Hierarchical local binary pattern for branch retinal vein occlusion recognition with fluorescein angiography images. Electronics Letters, 50(25), 1902-1904. doi: 10.1049/el.2014.2854

Keywords

  • Retinal recognition
  • Eye
  • Diagnostic radiography
  • Image representation
  • Diseases
  • Patient diagnosis
  • Medical image processing
  • Hierarchical local binary pattern
  • Branch retinal vein occlusion recognition
  • Fluorescein angiography images
  • BRVO
  • Retinal diseases
  • Automatic recognition
  • Feature representation method
  • HLBP
  • FA image dataset

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