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Deep Learning and the Future of Biomedical Image Analysis

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Deep Learning Techniques for Biomedical and Health Informatics

Part of the book series: Studies in Big Data ((SBD,volume 68))

Abstract

Deep Learning (DL) is popular among the researchers and academicians due to its reliability and accuracy, especially in the field of engineering and medical sciences. In the field of medical imaging for the diagnosis of disease, DL techniques are very helpful for early detection. Most important features of DL techniques are that they are uncomplicated with lower complexity, which ultimately saves the time and money and tackle many tough tasks simultaneously. Artificial Intelligence (AI) and Deep Learning (DL) technologies have rapidly improved in recent years. These techniques played an important role in every field of application, especially in the medical field such as in image processing, image fusion, image segmentation, image retrieval, image analysis, computer aided diagnosis (CAD), image registration and, image-guided therapy and many more. The aim of writing this chapter is to describe the DL methods and, the future of biomedical imaging using DL in detail and discuss the issues and challenges.

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Author information

Authors and Affiliations

  1. Central University of Rajasthan, Bandar Sindri, Ajmer, India

    Monika Jyotiyana & Nishtha Kesswani

Authors
  1. Monika Jyotiyana
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  2. Nishtha Kesswani
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Corresponding author

Correspondence to Monika Jyotiyana .

Editor information

Editors and Affiliations

  1. Department of Computer Science, North Orissa University, Takatpur, Odisha, India

    Sujata Dash

  2. School of Computer Science and Engineering, KIIT Deemed to University, Bhubaneswar, Odisha, India

    Biswa Ranjan Acharya

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

    Mamta Mittal

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, AL, USA

    Ajith Abraham

  5. Department of Organizational Systems and Adult Health, University of Maryland, Baltimore, MD, USA

    Arpad Kelemen

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Jyotiyana, M., Kesswani, N. (2020). Deep Learning and the Future of Biomedical Image Analysis. In: Dash, S., Acharya, B., Mittal, M., Abraham, A., Kelemen, A. (eds) Deep Learning Techniques for Biomedical and Health Informatics. Studies in Big Data, vol 68. Springer, Cham. https://doi.org/10.1007/978-3-030-33966-1_15

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