Deep Neural Networks for Multimodal Imaging and Biomedical Applications

Deep Neural Networks for Multimodal Imaging and Biomedical Applications

Indexed In: SCOPUS
Release Date: June, 2020|Copyright: © 2020 |Pages: 294
DOI: 10.4018/978-1-7998-3591-2
ISBN13: 9781799835912|ISBN10: 179983591X|EISBN13: 9781799835929
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Description & Coverage
Description:

The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques.

Deep Neural Networks for Multimodal Imaging and Biomedical Applications provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging. Featuring coverage on a broad range of topics such as prediction models, edge computing, and quantitative measurements, this book is ideally designed for researchers, academicians, physicians, IT consultants, medical software developers, practitioners, policymakers, scholars, and students seeking current research on biomedical advancements and developing computational methods in healthcare.

Coverage:

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

  • Biomedical Imaging
  • Convolutional Networks
  • Data Collection Methods
  • Edge Computing
  • Genetic Data Analysis
  • Machine Learning
  • Practical Healthcare Systems
  • Prediction Models
  • Quantitative Measurements
  • Visualization
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Editor/Author Biographies

A. Suresh, B.E., M.Tech., Ph.D works as the Professor & Head, Department of the Computer Science and Engineering in Nehru Institute of Engineering & Technology, Coimbatore, Tamil Nadu, India. He has been nearly two decades of experience in teaching and his areas of specializations are Data Mining, Artificial Intelligence, Image Processing, Multimedia and System Software. He has published two patents and 90 papers in International journals. He has book authored “Industrial IoT Application Architectures and use cases” published in CRC press and edited book entitled “Deep Neural Networks for Multimodal Imaging and Biomedical Application” published in IGI Global. He has currently editing three books namely “Deep learning and Edge Computing solutions for High Performance Computing” in EAI/Springer Innovations in Communications and Computing, “Sensor Data Management and Analysis: The Role of Deep Learning” and “Bioinformatics and Medical Applications: Big Data using Deep Learning Algorithms” in Scrivener-Wiley publisher. He has published 15 chapters in the book title An Intelligent Grid Network Based on Cloud Computing Infrastructures in IGI Global Publisher and Internet of Things for Industry 4.0 in EAI/Springer Innovations in Communication and Computing. He has published more than 40 papers in National and International Conferences. He has served as editor / reviewer for Springer, Elsevier, Wiley, IGI Global, IoS Press, Inderscience journals etc... He is a member of ISTE, MCSI, IACSIT, IAENG, MCSTA and Global Member of Internet Society (ISOC). He has organized several National Workshop, Conferences and Technical Events. He is regularly invited to deliver lectures in various programmes for imparting skills in research methodology to students and research scholars. He has published four books, in the name of Data structures & Algorithms, Computer Programming, Problem Solving and Python Programming and Programming in “C” in DD Publications, Excel Publications and Sri Maruthi Publisher, Chennai, respectively. He has hosted two special sessions for IEEE sponsored conference in Osaka, Japan and Thailand.

R. Udendhran computer science researcher on Deep learning. He worked as a data scientist and presented research work in an international conference held at the University of Cambridge which is available in the ACM digital library. He has published research papers in international journals and his research area extensively focuses deep learning. He has completed M.Tech in computer science and engineering. His research work focuses on deep learning and cryptography.

S. Vimal is working in Department of Information Technology, National Engineering College, Kovilpatti, Tamilnadu, India. He has around Fourteen years of teaching experience and research experience.He is a EMC certified Data science Associate and CCNA certified professional too. He holds a Ph.D in Information and Communication Engineering from Anna University Chennai and he received Masters Degree from Anna University Coimbatore. He is a member of various professional bodies and organized various funded workshops ,seminars from DST,DBT.AICTE. He has wide publications in the highly impact journals in the area of Data Analytics, Networking and Security issues and published 04 book chapters. He has hosted two special session for IEEE sponsored conference in Osaka, Japan and Thailand. He has acted as Session chair,organizing committee member, advisory committee and outreach committee member in various international conferences supported by IEEE. His areas of interest include Game Modelling, Artificial Intelligence, Cognitive radio networks, Network security, Machine Learning and Big data Analytics. He is a Senior member in IEEE and holds membership in various professional bodies. He has served as Guest Editor, reviewer for IEEE,Springer, Elsevier and Wiley journals.

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