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Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2024
ISBN 10: 3031637801 ISBN 13: 9783031637803
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Verlag: Springer Nature Switzerland AG, Cham, 2021
ISBN 10: 3030666328 ISBN 13: 9783030666323
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Hardcover. Zustand: new. Hardcover. This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of thestate-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things. This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Sprache: Englisch
Verlag: Springer International Publishing AG, Cham, 2025
ISBN 10: 3031987276 ISBN 13: 9783031987274
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Hardcover. Zustand: new. Hardcover. This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Sprache: Englisch
Verlag: Elsevier Science Publishing Co Inc, 2024
ISBN 10: 0443137927 ISBN 13: 9780443137921
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Sprache: Englisch
Verlag: Springer International Publishing AG, Cham, 2025
ISBN 10: 3031987276 ISBN 13: 9783031987274
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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In den WarenkorbHardcover. Zustand: Brand New. 270 pages. 9.26x6.11x9.49 inches. In Stock.