Overview
- Offers a valuable reference guide for both students and professional researchers in related fields of medical imaging and computer-aided diagnosis (CAD)
- Interprets current trends in the field and makes them accessible to a broad readership
- Combines hot-topic discussions with in-depth analysis
Part of the book series: Lecture Notes in Electrical Engineering (LNEE, volume 633)
Included in the following conference series:
Conference proceedings info: MICAD 2020.
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About this book
This book covers virtually all aspects of image formation in medical imaging, including systems based on ionizing radiation (x-rays, gamma rays) and non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike. In addition, it discusses the development and application of computer-aided detection and diagnosis (CAD) systems in medical imaging.
Given its coverage, the book provides both a forum and valuable resource for researchers involved in image formation, experimental methods, image performance, segmentation, pattern recognition, feature extraction, classifier design, machine learning / deep learning, radiomics, CAD workstation design, human–computer interaction, databases, and performance evaluation.
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Keywords
Table of contents (24 papers)
Other volumes
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Medical Imaging and Computer-Aided Diagnosis
Editors and Affiliations
About the editors
Dr. Ruidan Su received his M.Sc. in Software Engineering from Northeastern University, China, in 2010, and his Ph.D. degree in Computer Application Technology from Northeastern University, China, in 2014. He is currently an Assistance Professor of Shanghai Advanced Research Institute, Chinese Academy of Sciences. His field of science is digital image processing and artificial intelligence, video system processing, machine learning, computational intelligence, software engineering, data analytics, system optimization, and multi-population genetic algorithm.
Dr. Ruidan Su is an IEEE Senior Member. He has published 22 papers in refereed journals and conference proceedings. He was the Founder & Editor-in-Chief of Journal of Computational Intelligence and Electronic Systems published by American Scientific Publisher from 2012 to 2016. He was an Associate Editor for the Journal of Granular Computing Published by Springer, an Associate Editor for the Journal of Intelligent& Fuzzy Systems published by IOS Press, and a Review Board Member for Applied Intelligence.
Dr. Ruidan Su was the Guest Editor for Multimedia Tools and Applications by Springer for Special Issue on Practical Augmented Reality (AR) Technology and its Applications, a Guest Editor for the Journal of International Journal of Hydrogen Energy, and a Proceeding Editor for the Proceeding of 2018 & 2019 International Conference on Image and Video Processing, and Artificial Intelligence (IVPAI 2018 & 2019, published by SPIE). He was a Conference Chair for 2018 & 2019 International Conference on Image and Video Processing, and Artificial Intelligence, a conference Chair for 2018 3rd International Conference on Computer, Communication and Computational Sciences, and a Conference Program Committee Member for 18th International Conference on Machine Learning and Cybernetics
Dr. Ruidan Su has been a Reviewer for several leading journals, such as Information Sciences, IEEETransactions on Cybernetics, IEEE Access, Applied Intelligence, International Journal of Pattern Recognition and Artificial Intelligence, Knowledge and Information Systems, Multimedia Tools and Application, The Journal of Supercomputing, Concurrency and Computation: Practice and Experience, and Electronic Commerce Research.
Han Liu is currently a Research Associate in Data Science in the School of Computer Science and Informatics at Cardiff University. He has previously been a Research Associate in Computational Intelligence in the School of Computing at the University of Portsmouth. He received a B.Sc. in Computing from the University of Portsmouth in 2011, an M.Sc. in Software Engineering from the University of Southampton in 2012, and a Ph.D. in Machine Learning from the University of Portsmouth in 2015. His research interests are in artificial intelligence in general and machine learning in particular. His other related areas include sentiment analysis, pattern recognition, intelligent systems, big data, granular computing, and computational intelligence.
He has published two research monographs in Springer and over 60 papers in the areas such as data mining, machine learning, and intelligent systems. One of his papers was identified as a key scientific article contributing to scientific and engineering research excellence by the selection team at Advances in Engineering and the selection rate is less than 0.1%. He also has three papers selected, respectively, as finalists of Lotfi Zadeh Best Paper Award in the 16th, 17th, and 18th International Conference on Machine Learning and Cybernetics (ICMLC 2017, 2018 & 2019).
Bibliographic Information
Book Title: Medical Imaging and Computer-Aided Diagnosis
Book Subtitle: Proceeding of 2020 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2020)
Editors: Ruidan Su, Han Liu
Series Title: Lecture Notes in Electrical Engineering
DOI: https://doi.org/10.1007/978-981-15-5199-4
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2020
Hardcover ISBN: 978-981-15-5198-7Published: 03 July 2020
Softcover ISBN: 978-981-15-5201-4Published: 03 July 2021
eBook ISBN: 978-981-15-5199-4Published: 02 July 2020
Series ISSN: 1876-1100
Series E-ISSN: 1876-1119
Edition Number: 1
Number of Pages: X, 244
Number of Illustrations: 31 b/w illustrations, 76 illustrations in colour
Topics: Biomedical Engineering and Bioengineering, Signal, Image and Speech Processing, Image Processing and Computer Vision, Pattern Recognition, Diagnostic Radiology