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Performance Analysis of Convolutional Neural Networks for Exudate Detection in Fundus Images

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Intelligent Computing and Communication (ICICC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1034))

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Abstract

In the diagnosis of diabetic retinopathy and macula edema, the extraction of exudates is a crucial task, particularly in the presence of optic disc and cotton wools which have similar intensity. To add to this some of the reflectance around the vessels originating from the optic disc also needs to be eliminated. In this paper, supervised method with deep learning neural network is proposed for exudate classification. The network is trained with large number of sub-images, around 48,000 for each image, which are fed as inputs to the network. The original image is pre-processed before the patches are extracted. The database e-Ophtha is used. It has 47 images with exudates and ground truths. The performance of the system is good with an accuracy of 98.67%, area under the curve 97.29, sensitivity of 72.26% and specificity of 98.76%. Analysis of the system with respect to depth of network and patch size is also performed.

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Authors and Affiliations

  1. Research Scholar, Fr. Conceicao Rodrigues College of Engineering, Mumbai, 400050, Maharashtra, India

    Nandana Prabhu

  2. Professor, Department of Electronics Engineering, Fr. Conceicao Rodrigues College of Engineering, Mumbai, 400050, Maharashtra, India

    Deepak Bhoir

  3. Retired Professor, Department of Electronics Engineering, Shah and Anchor Kutchhi Engineering College, Mumbai, 400088, Maharashtra, India

    Uma Rao

Authors
  1. Nandana Prabhu
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  2. Deepak Bhoir
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  3. Uma Rao
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Corresponding author

Correspondence to Nandana Prabhu .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  2. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  3. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

  4. Department of MCA, J. S. S. Science and Technology University, Mysuru, India

    V. N. Manjunath Aradhya

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Prabhu, N., Bhoir, D., Rao, U. (2020). Performance Analysis of Convolutional Neural Networks for Exudate Detection in Fundus Images. In: Bhateja, V., Satapathy, S., Zhang, YD., Aradhya, V. (eds) Intelligent Computing and Communication. ICICC 2019. Advances in Intelligent Systems and Computing, vol 1034. Springer, Singapore. https://doi.org/10.1007/978-981-15-1084-7_36

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