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Hierarchical Local Binary Pattern for Branch Retinal Vein Occlusion Recognition

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Computer Vision - ACCV 2014 Workshops (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9008))

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Abstract

Branch retinal vein occlusion (BRVO) is one of the most common retinal vascular diseases of the elderly that would dramatically impair one’s vision if it is not diagnosed and treated timely. Automatic recognition of BRVO could significantly reduce an ophthalmologist’s workload, make the diagnosis more efficient, and save the patients’ time and costs. In this paper, we propose for the first time, to the best of our knowledge, automatic recognition of BRVO using fundus images. In particular, we propose Hierarchical Local Binary Pattern (HLBP) to represent the visual content of an fundus image for classification. HLBP is comprised of Local Binary Pattern (LBP) in a hierarchical fashion with max-pooling. In order to evaluate the performance of HLBP, we establish a BRVO dataset for experiments. HLBP is compared with several state-of-the-art feature presentation methods on the BRVO dataset. Experimental results demonstrate the superior performance of our proposed method for BRVO recognition.

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Notes

  1. 1.

    The dataset can be downloaded on: http://pan.baidu.com/s/1ntohK5V.

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Acknowledgement

This work was supported by a research grant from The Hong Kong Polytechnic University (Project Code: G-YL77). The authors thank Yancheng Third People’s Hospital for providing the BRVO and normal color fundus images.

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Authors and Affiliations

  1. Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, kowloon, Hong Kong

    Zenghai Chen, Zheru Chi & Hong Fu

  2. Yancheng Institute of Health Sciences, Yancheng, Jiangsu, China

    Hui Zhang

  3. Department of Computer Science, Chu Hai College of Higher Education, kowloon, Hong Kong

    Hong Fu

Authors
  1. Zenghai Chen
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  2. Hui Zhang
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  3. Zheru Chi
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  4. Hong Fu
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Corresponding author

Correspondence to Zenghai Chen .

Editor information

Editors and Affiliations

  1. Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, India

    C.V. Jawahar

  2. Institue of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

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Chen, Z., Zhang, H., Chi, Z., Fu, H. (2015). Hierarchical Local Binary Pattern for Branch Retinal Vein Occlusion Recognition. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9008. Springer, Cham. https://doi.org/10.1007/978-3-319-16628-5_49

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  • DOI: https://doi.org/10.1007/978-3-319-16628-5_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16627-8

  • Online ISBN: 978-3-319-16628-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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