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

Hui Zhang, Zenghai Chen, Zheru Chi, Hong Fu

Research output: Journal article publicationJournal articleAcademic researchpeer-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 maxpooling. 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.
Original languageEnglish
Pages (from-to)1902-1904
Number of pages3
JournalElectronics Letters
Volume50
Issue number25
DOIs
Publication statusPublished - 1 Jan 2014

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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