Today's healthcare organizations must focus on a lot more than just the health of their clients. The infrastructure it takes to support clinical-care delivery continues to expand, with information technology being one of the most significant contributors to that growth. As companies have become more dependent on technology for their clinical, administrative, and financial functions, their IT departments and expenditures have had to scale quickly to keep up. However, as technology demands have increased, so have the options for reliable infrastructure for IT applications and data storage. The one that has taken center stage over the past few years is cloud computing. Healthcare researchers are moving their efforts to the cloud because they need adequate resources to process, store, exchange, and use large quantities of medical data.
Cloud Computing in Medical Imaging covers the state-of-the-art techniques for cloud computing in medical imaging, healthcare technologies, and services. The book focuses on
Machine-learning algorithms for health data security
Fog computing in IoT-based health care
Medical imaging and healthcare applications using fog IoT networks
Diagnostic imaging and associated services
Image steganography for medical informatics
This book aims to help advance scientific research within the broad field of cloud computing in medical imaging, healthcare technologies, and services. It focuses on major trends and challenges in this area and presents work aimed to identify new techniques and their use in biomedical analysis.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Academic and Postgraduate
Illustrationen
88 s/w Abbildungen, 35 s/w Photographien bzw. Rasterbilder, 53 s/w Zeichnungen
53 Line drawings, black and white; 35 Halftones, black and white; 88 Illustrations, black and white
Maße
Höhe: 240 mm
Breite: 161 mm
Dicke: 20 mm
Gewicht
ISBN-13
978-0-367-70239-7 (9780367702397)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Ayman El-Baz, Ph.D., Professor, University Scholar, and Chair of Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master degrees in Electrical Engineering in 1997 and 2001. He earned his doctoral degrees in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contribution in the biomedical translational research. Dr El-Baz has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 300 technical articles (87 journals, 9 books, 39 book chapters, 144 refereed-conference papers, 74 abstracts published in proceedings, and 12 US patents).
Jasjit S. Suri, an innovator, a visionary, a scientist, and an internationally-known world leader, has spent about 30 years in the field of biomedical engineering/sciences, software and hardware engineering and its management. During his career in biomedical industry/imaging, he has had an upstream growth and responsibilities from scientific Engineer, Scientist, Manager, Director R&D, Sr. Director, Vice President, Chief Technology Officer (CTO), CEO level positions in industries like Siemens Medical Systems, Philips Medical Systems, Fisher Imaging Corporation and Eigen Inc., Global Biomedical Technologies Inc., AtheroPoint (TM), respectively and managed unto a maximum of 50 to 100 people. He is currently the Chairman of Global Biomedical Technologies, Inc., CA, USA.
Herausgeber*in
University of Louisville, Kentucky, USA
Acknowledgements. Preface. Editors. Contributors. 1 Cloud Computing in Healthcare and Medical Imaging: A Brief Overview. 2 ISM and DEMATEL Analysis of H4.0 Enablers in the Indian Healthcare Industry. 3 Machine Learning Algorithms for Health Data Security: A Systematic Review. 4 Fog Computing in IoT-Based Healthcare Systems. 5 Medical Imaging and Healthcare Applications Using 5G. 6 The Application of Cloud-Computing Technology to Improve Patients' Medical History Access to Clinicians for Quality of Care in the Fourth Industrial Revolution. 7 Diagnostic Imaging and Associated Services: Toward Interoperability and Cloud Computing. 8 Health Monitoring Based on the Integrated Offer of Cloud-IoT Sensing Services. 9 Sleep-Stage Identification Using Recurrent Neural Network for ECG Wearable-Sensor Systems. 10 Classification of Methods to Reduce Clinical Alarm Signals for Remote Patient Monitoring: A Critical Review. 11 Cloud Computing in Medical Imaging, Healthcare Technologies, and Services. 12 An Insight into Image Steganography for Medical Informatics. Index.
