Artificial Intelligence and Big Data for Medical Image Processing

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Authors

M Akshara Vijayan
Department of Computer Science and Engineering, St. Joseph's College of Engineering and Technology
https://orcid.org/0009-0002-5117-6033
R Jayashree
Department of Computer Science and Engineering, St. Joseph's College of Engineering and Technology
https://orcid.org/0009-0006-9419-4556

Keywords:

Artificial Intelligence, Big Data, Medical Image Processing, Deep Learning, Medical Imaging, Smart Healthcare, IoT in Healthcare

Synopsis

Medical imaging has become an indispensable tool in modern healthcare, enabling clinicians to visualize internal structures of the human body and detect diseases at early stages. With the explosive growth of healthcare data and the advancements in artificial intelligence (AI), the integration of big data technologies with medical image processing has opened new horizons for research, clinical applications, and decision support systems.

This book aims to provide students, researchers, and professionals with a comprehensive yet concise understanding of how AI and big data are transforming the field of medical imaging. The chapters cover fundamental concepts, state-of-the-art techniques, real-world applications, and emerging challenges, making the book both an academic reference and a practical guide.

We have structured the book to gradually build knowledge — beginning with the basics of medical image processing, progressing through machine learning and deep learning techniques, and culminating with advanced applications and future directions. Each chapter is enriched with examples, case studies, and references to ensure readers gain both theoretical insight and practical exposure.

This work is intended for:

  • Undergraduate and postgraduate students of computer science, biomedical engineering, and related fields
  • Researchers working on artificial intelligence, big data, and healthcare applications
  • Professionals seeking to understand the role of AI and big data in medical imaging systems

It is our hope that this book inspires readers to contribute to the next generation of intelligent healthcare solutions.

References

Razzak, M.I., Imran, M., & Xu, G. (2018). Big data analytics for preventive medicine. Neural Computing and Applications, 32(9), 4417–4451. https://doi.org/10.1007/s00521-017-3279-0

Litjens, G., Kooi, T., Bejnordi, B.E., et al. (2017). A survey on deep learning in medical image analysis. Medical Image Analysis, 42, 60–88. https://doi.org/10.1016/j.media.2017.07.005

Lundervold, A.S., & Lundervold, A. (2019). An overview of deep learning in medical imaging focusing on MRI. Zeitschrift für Medizinische Physik, 29(2), 102–127. https://doi.org/10.1016/j.zemedi.2018.11.002

Apache Software Foundation. (2023). Apache Spark™ Programming Guide. Retrieved from https://spark.apache.org/docs/latest/

Dean, J., & Ghemawat, S. (2008). MapReduce: Simplified data processing on large clusters. Communications of the ACM, 51(1), 107–113. https://doi.org/10.1145/1327452.1327492

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Published

15 September 2025
Copyright (c) 2025 M Akshara Vijayan, R Jayashree

Details about the available publication format: E-Book

E-Book

ISBN-13 (15)

978-93-7185-033-9

Details about the available publication format: Book (Paperback)

Book (Paperback)

ISBN-13 (15)

978-93-7185-784-0

How to Cite

Vijayan, M. A. ., & Jayashree, R. . (2025). Artificial Intelligence and Big Data for Medical Image Processing. Deep Science Publishing. https://doi.org/10.70593/978-93-7185-033-9
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