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U-Net Based Optic Cup and Disk Segmentation from Retinal Fundus Images via Entropy Sampling

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Advanced Computational Paradigms and Hybrid Intelligent Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1373))

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Abstract

Accurate identification of optical disk and cup regions plays a vital role in clinically detection of retinal diseases. Diagnosis of severe ophthalmic pathologies can be made by proper detection of optical disk and cup. The most common method used for ocular screening is color fundus image (CFI). From this CFI, the cup-to-disk (CDR) ratio can be calculated correctly after proper detection of disk–cup regions, and this CDR plays important clues for glaucoma detection. This paper presents an entropy-based deep learning approach to perform such accurate segmentation from digital retinal images. The performance of the proposed approach exhibits promising results in comparison to prior existing methods on two dataset Drishti-GS and RIM-ONE V3.

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Acknowledgements

The authors are grateful to Dr. Sumit Banerjee (Director, Megha Eye Centre, Purba Bardhaman, West Bengal) for providing valuable input and feedback for this work.

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Authors and Affiliations

  1. Department of Information Technology, University Institute of Technology, Burdwan, India

    Arindam Chowdhury & Alloy Das

  2. Department of Computer Science, University Institute of Technology, Burdwan, India

    Rohit Agarwal

  3. Department of Computer Science, National Institute of Technology, Durgapur, India

    Debashis Nandi

Authors
  1. Arindam Chowdhury
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  2. Rohit Agarwal
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  3. Alloy Das
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  4. Debashis Nandi
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology, New Delhi, Delhi, India

    Tapan Kumar Gandhi

  2. Department of Computer Science and Engineering, SRM University, Amaravati, Andhra Pradesh, India

    Debanjan Konar

  3. Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Majitar, Sikkim, India

    Biswaraj Sen

  4. Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Majitar, Sikkim, India

    Kalpana Sharma

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Chowdhury, A., Agarwal, R., Das, A., Nandi, D. (2022). U-Net Based Optic Cup and Disk Segmentation from Retinal Fundus Images via Entropy Sampling. In: Gandhi, T.K., Konar, D., Sen, B., Sharma, K. (eds) Advanced Computational Paradigms and Hybrid Intelligent Computing . Advances in Intelligent Systems and Computing, vol 1373. Springer, Singapore. https://doi.org/10.1007/978-981-16-4369-9_47

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