Future of AI in Medical Imaging

Future of AI in Medical Imaging

Release Date: March, 2024|Copyright: © 2024 |Pages: 312
DOI: 10.4018/979-8-3693-2359-5
ISBN13: 9798369323595|EISBN13: 9798369323601
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Description & Coverage
Description:

Academic scholars and professionals are currently grappling with hurdles in optimizing diagnostic processes, as traditional methodologies prove insufficient in managing the intricate and voluminous nature of medical data. The diverse range of imaging techniques, spanning from endoscopy to magnetic resonance imaging, necessitates a more unified and efficient approach. This complexity has created a pressing need for streamlined methodologies and innovative solutions. Academic scholars find themselves at the forefront of addressing these challenges, seeking ways to leverage AI's full potential in improving the accuracy of medical imaging diagnostics and, consequently, enhancing overall patient outcomes.

Future of AI in Medical Imaging, stands as a solution to the challenges faced by academic scholars in the realm of medical imaging. The book lays a solid groundwork for understanding the complexities of medical imaging systems. Through an exploration of various imaging modalities, it not only addresses the current issues but also serves as a guide for scholars to navigate the landscape of AI-integrated medical diagnostics. This collaborative effort not only illuminates the existing hurdles of medical imaging but also looks towards a future where AI-driven diagnostics and personalized medicine become indispensable tools, significantly elevating patient outcomes.

For scholars seeking to contribute to this subject area, Future of AI in Medical Imaging serves as a resource to learn about new ideas, methodologies, and technological advancements. By fostering interdisciplinary collaboration and encouraging a global exchange of insights, the book positions itself as a tool for innovation in the intersection of AI and medical imaging. Through the inspiration of curiosity, it calls on scholars, researchers, and professionals to collectively engage in resolving the challenges associated with leveraging AI in medical imaging.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Advanced Techniques for Image Formation
  • Bridging Science and Healthcare
  • Elevating Patient Outcomes
  • Emerging Trends in Medical Imaging
  • Endoscopy
  • Evolution of Medical Imaging
  • Healthcare Technology Transformation
  • New Perspectives in Medical Imaging
  • Personalized Medicine
  • System Theory in Medical Imaging
  • The Role of Image Processing
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Editor/Author Biographies
Dr. Avinash Kumar Sharma currently working as Associate Professor, Department of Computer Science & Engineering, Sharda School of Engineering & Technology (SSET), Sharda University., Greater Noida. My research areas are Cloud Computing, Machine Learning, Smart Agriculture, Artificial Intelligence. I have 17 years of teaching experience. I have published about 25 research papers in national / international conferences, journals and book chapters. I have published 03 patents including 01 design patents.
Nitin Chanderwal is currently working as an Associate Professor Educator-Full Time in the Department of Electrical and Computer Engineering at University of Cincinnati. In the past I have worked as Associate Professor-Full Time of Information Systems and Analytics at IIM Shillong, Meghalaya, INDIA. During his tenure at IIM Shillong he also served as Chairperson for the Areas: {(Information Systems and Analytics) & (IT Services and Website Committee)}. During 2017-2018, He has worked as Professor Educator in the Department of EECS at University of Cincinnati, OH and during 2010-2011 as First Tier Bank Professor in the Peter Kiewit Institute at University of Nebraska at Omaha, NE, USA. In July 2001, he received B.Engg. in Computer Science & Engineering [Hons.] from Dr. B.R. Ambedkar University, Agra and M.Engg. in Software Engineering from Thapar University, erstwhile Thapar Institute of Engineering and Technology (Deemed University), Patiala, Punjab, INDIA in March 2003. In September 2008, he received Ph.D. in Computer Science & Engineering from Jaypee University of Information Technology, INDIA and University of Florida (UF), Gainesville, FL, USA under student exchange program, specifically he has completed 12 credits course work from UF. In May 2013, he received D.Sc. in Computer Science & Engineering from Uttarakhand Technical University, Dehradun, INDIA. I completed partial research work of D.Sc. at University of Nebraska at Omaha (UNO), NE, USA. He is a IBM certified engineer, a Life Member of IAENG, Senior Member of IEEE, ACM & IACSIT and Member of SIAM and ACIS and have published 200+ Research Papers in peer reviewed International Journals & Transactions, Book Chapters, Symposium, Conferences and Position. He has bagged more than 50 academic and research awards. My research interest includes Blockchain Technology, Cyber Physical Systems, Big Data Analytics, Social Networks especially Computer Mediated Communications & Flaming, Interconnection Networks & Architecture, Fault-tolerance & Reliability, NoCs, SoCs, and NiPs, Application of Stable Matching Problems, Stochastic Communication and Sensor Networks. He has received 2 Indian Patents and 1 Australian Patent during 2020-2021. he is also an Associate Editor of the International Journal of Parallel, Emergent and Distributed Systems, Taylor and Francis, UK and IEEE Access, IEEE, USA.

Shobhit Tyagi is currently affiliated with Sharda University.

Prashant Upadhyay is currently affiliated with Sharda University.

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