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Deep Learning and Its Applications in Medical Imaging

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Internet of Things for Healthcare Technologies

Part of the book series: Studies in Big Data ((SBD,volume 73))

Abstract

Big data are information assets characterized by high volume, velocity, variety, and veracity. Large, multilevel, and integrated datasets offer the promise of unlocking novel insights and accelerating breakthroughs. According to an increasing interest in artificial intelligence around the world, deep learning has attracted a great deal of public attention. Deep learning techniques increase learning capacity and provide a decision support system at scales that are transforming the future of health care. Every day, deep learning algorithms are used broadly across different industries. The latest advances in deep learning technologies provide new effective paradigms to obtain end-to-end learning models from intricate data. This chapter explains what deep learning is and why it is so important. We provide several examples where deep learning techniques find applications and what kind of problems can be solved using deep learning in medical imaging. This chapter also introduces a particular type of deep learning algorithm, including autoencoders, restricted Boltzmann machines, deep belief network, recurrent neural networks, and convolutional neural networks with practical variant case studies, which are at the basis of deep learning.

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Author information

Authors and Affiliations

  1. Faculty of Management and Accounting, Department of Industrial Management, Allameh Tabataba’i University, West End Hemmat Highway, Dehkadeh-ye-Olympic, 1489684511, Tehran, Iran

    Farzaneh Mansouri Musolu, Saeid Sadeghi Darvazeh & Iman Raeesi Vanani

Authors
  1. Farzaneh Mansouri Musolu
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  2. Saeid Sadeghi Darvazeh
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  3. Iman Raeesi Vanani
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Corresponding author

Correspondence to Farzaneh Mansouri Musolu .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, India

    Chinmay Chakraborty

  2. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Amit Banerjee

  3. Department of Electrical Engineering, Indian Institute of Technology Patna, Patna, India

    Maheshkumar H. Kolekar

  4. Department of Computer Information Systems, Faculty of Information and Communication Technology, University of Malta, Msida, Malta

    Lalit Garg

  5. Faculty of Software and Information Science, Iwate Prefectural University, Takizawa, Japan

    Basabi Chakraborty

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Mansouri Musolu, F., Sadeghi Darvazeh, S., Raeesi Vanani, I. (2021). Deep Learning and Its Applications in Medical Imaging. In: Chakraborty, C., Banerjee, A., Kolekar, M., Garg, L., Chakraborty, B. (eds) Internet of Things for Healthcare Technologies. Studies in Big Data, vol 73. Springer, Singapore. https://doi.org/10.1007/978-981-15-4112-4_7

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