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Biomedical Signal and Image Processing in Patient Care

Author: Kolekar, Maheshkumar H.

Publisher: IGI Global

Published: 2017-08-11

Total Pages: 312

ISBN-13: 152252830X

In healthcare systems, medical devices help physicians and specialists in diagnosis, prognosis, and therapeutics. As research shows, validation of medical devices is significantly optimized by accurate signal processing. Biomedical Signal and Image Processing in Patient Care is a pivotal reference source for progressive research on the latest development of applications and tools for healthcare systems. Featuring extensive coverage on a broad range of topics and perspectives such as telemedicine, human machine interfaces, and multimodal data fusion, this publication is ideally designed for academicians, researchers, students, and practitioners seeking current scholarly research on real-life technological inventions.

Biomedical Signal and Image Processing

Author: Kayvan Najarian

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 411

ISBN-13: 1439870349

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Written for senior-level and first year graduate students in biomedical signal and image processing, this book describes fundamental signal and image processing techniques that are used to process biomedical information. The book also discusses application of these techniques in the processing of some of the main biomedical signals and images, such as EEG, ECG, MRI, and CT. New features of this edition include the technical updating of each chapter along with the addition of many more examples, the majority of which are MATLAB based.

Biomedical Signal Processing for Healthcare Applications

Author: Varun Bajaj

Publisher: CRC Press

Published: 2021-07-21

Total Pages: 336

ISBN-13: 1000413306

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This book examines the use of biomedical signal processing—EEG, EMG, and ECG—in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights of Biomedical Signal Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications. FEATURES Examines modeling and acquisition of biomedical signals of different disorders Discusses CAD-based analysis of diagnosis useful for healthcare Includes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCG Includes case studies and research directions, including novel approaches used in advanced healthcare systems This book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

Biosignal and Medical Image Processing

Author: John L. Semmlow

Publisher: CRC Press

Published: 2021-10-01

Total Pages: 630

ISBN-13: 1466567376

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Written specifically for biomedical engineers, Biosignal and Medical Image Processing, Third Edition provides a complete set of signal and image processing tools, including diagnostic decision-making tools, and classification methods. Thoroughly revised and updated, it supplies important new material on nonlinear methods for describing and classify

Biomedical Signal Processing and Artificial Intelligence in Healthcare

Author: Walid A. Zgallai

Publisher: Academic Press

Published: 2020-07-29

Total Pages: 270

ISBN-13: 0128189479

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Biomedical Signal Processing and Artificial Intelligence in Healthcare is a new volume in the Developments in Biomedical Engineering and Bioelectronics series. This volume covers the basics of biomedical signal processing and artificial intelligence. It explains the role of machine learning in relation to processing biomedical signals and the applications in medicine and healthcare. The book provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of Deep Learning, Neural Networks, and the implications of the expansion of artificial intelligence is covered. Biomedical Images are also introduced and processed, including segmentation, classification, and detection. This book covers different aspects of signals, from the use of hardware and software, and making use of artificial intelligence in problem solving.Dr Zgallai’s book has up to date coverage where readers can find the latest information, easily explained, with clear examples and illustrations. The book includes examples on the application of signal and image processing employing artificial intelligence to Alzheimer, Parkinson, ADHD, autism, and sleep disorders, as well as ECG and EEG signals. Developments in Biomedical Engineering and Bioelectronics is a 10-volume series which covers recent developments, trends and advances in this field. Edited by leading academics in the field, and taking a multidisciplinary approach, this series is a forum for cutting-edge, contemporary review articles and contributions from key ‘up-and-coming’ academics across the full subject area. The series serves a wide audience of university faculty, researchers and students, as well as industry practitioners. Coverage of the subject area and the latest advances and applications in biomedical signal processing and Artificial Intelligence Contributions by recognized researchers and field leaders On-line presentations, tutorials, application and algorithm examples

Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems

Author: E. Priya

Publisher: Springer Nature

Published: 2020-09-21

Total Pages: 290

ISBN-13: 9811561419

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This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.

Signal and Image Processing in Medical Applications

Author: Amit Kumar

Publisher: Springer

Published: 2016-04-08

Total Pages: 0

ISBN-13: 9789811006890

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This book highlights recent findings on and analyses conducted on signals and images in the area of medicine. The experimental investigations involve a variety of signals and images and their methodologies range from very basic to sophisticated methods. The book explains how signal and image processing methods can be used to detect and forecast abnormalities in an easy-to-follow manner, offering a valuable resource for researchers, engineers, physicians and bioinformatics researchers alike.

Classification and Clustering in Biomedical Signal Processing

Author: Dey, Nilanjan

Publisher: IGI Global

Published: 2016-04-07

Total Pages: 463

ISBN-13: 152250141X

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Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research findings in the areas of signal processing for biomedical applications with an emphasis on classification and clustering techniques, this essential publication is designed for use by medical professionals, IT developers, and advanced-level graduate students.

Biomedical Signal and Image Processing

Author: Kayvan Najarian

Publisher: CRC Press

Published: 2005-12-21

Total Pages: 458

ISBN-13: 142005807X

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All of the biomedical measurement technologies, which are now instrumental to the medical field, are essentially useless without proper signal and image processing. Biomedical Signal and Image Processing is unique in providing a comprehensive survey of all the conventional and advanced imaging modalities and the main computational methods used for

Biomedical Signal and Image Examination with Entropy-Based Techniques

Author: V. Rajinikanth

Publisher: CRC Press

Published: 2020-12-21

Total Pages: 135

ISBN-13: 1000327256

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The aim of this book is to outline the concept of entropy, various types of entropies and their implementation to evaluate a variety of biomedical signals/images. The book emphasizes various entropy-based image pre-processing methods which are essential for the development of suitable computerized examination systems. The recent research works on biomedical signal evaluation confirms that signal analysis provides vital information regarding the physiological condition of the patient, and the efficient evaluation of these signals can help to diagnose the nature and the severity of the disease. This book emphasizes various entropy-based image pre-processing methods which are essential for the development of suitable computerized examination systems for the analysis of biomedical images recorded with a variety of modalities. The work discusses the image pro-processing methods with the Entropies, such as Kapur, Tsallis, Shannon and Fuzzy on a class of RGB-scaled and gray-scaled medical pictures. The performance of the proposed technique is justified with the help of suitable case studies, which involves x-ray image analysis, MRI analysis and CT analysis. This book is intended for medical signal/image analysts, undergraduate and postgraduate students, researchers, and medical scientists interested in biomedical data evaluation.