Springer Medical Imaging and Computer-Aided Diagnosis: Proceeding of 2020 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD ... Notes in Electrical Engineering, 633)

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.  From the Back Cover 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.  About the Author 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, IEEE Transactions 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 Scienc