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Artificial Intelligence Based Glaucoma Detection

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Advancement of Machine Intelligence in Interactive Medical Image Analysis

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

Artificial Intelligence has shown significant enhancement recently, in many fields, especially in pattern recognition in computer vision and hence in medical diagnosis, wherein highly accurate automated diseases diagnosis has now become feasible. Artificial Intelligence methods, especially based on deep learning are very powerful and have got huge training and learning potential. These methods are growing from strength to strength and far exceeding the performance of traditional methods. The deep learning has proved to be highly efficient and accurate especially when balanced and large training data is available. This chapter provides an overview of various Artificial Intelligence based techniques for detection of the second-largest disease which causes blindness, that is, glaucoma. The chapter begins with the introduction of glaucoma and the various important parameters required for its accurate diagnosis. The later sections introduce various traditional Machine learning based techniques, followed by Deep learning based techniques including the Transfer learning and Ensemble learning based techniques in use for automated glaucoma detection, along with their advantages and drawbacks. This chapter also exposes readers to original and genuine data of perimetry and OCT tests.

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Authors and Affiliations

  1. C-DAC Mohali, A-34 Industrial Area, Phase VIII, Mohali, 160071, Punjab, India

    Prabhjot Kaur & Praveen Kumar Khosla

Authors
  1. Prabhjot Kaur
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  2. Praveen Kumar Khosla
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Corresponding author

Correspondence to Prabhjot Kaur .

Editor information

Editors and Affiliations

  1. G. B. Pant Government Engineering College, Okhla, New Delhi, India

    Om Prakash Verma

  2. Washington University in St. Louis, St. Louis, MO, USA

    Sudipta Roy

  3. Birla Institute of Technology, Mesra (Patna Campus), Patna, Bihar, India

    Subhash Chandra Pandey

  4. Department of Computer Science and Engineering, G. B. Pant Government Engineering College, New Delhi, Delhi, India

    Mamta Mittal

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Kaur, P., Khosla, P.K. (2020). Artificial Intelligence Based Glaucoma Detection. In: Verma, O., Roy, S., Pandey, S., Mittal, M. (eds) Advancement of Machine Intelligence in Interactive Medical Image Analysis. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-1100-4_14

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