Classification And Clustering In Biomedical Signal Processing
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Classification And Clustering In Biomedical Signal Processing
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Author : Dey, Nilanjan
language : en
Publisher: IGI Global
Release Date : 2016-04-07
Classification And Clustering In Biomedical Signal Processing written by Dey, Nilanjan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-07 with Technology & Engineering categories.
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
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Author : Kayvan Najarian
language : en
Publisher: CRC Press
Release Date : 2005-12-21
Biomedical Signal And Image Processing written by Kayvan Najarian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-21 with Medical categories.
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 processing the data obtained from each. This book offers self-contained coverage of the mathematics and biology/physiology necessary to build effective algorithms and programs for biomedical signal and image processing applications. The first part of the book details the main signal and image processing, pattern recognition, and feature extraction techniques along with computational methods from other fields such as information theory and stochastic processes. Building on this foundation, the second part explores the major one-dimensional biological signals, the biological origin and importance of each signal, and the commonly used processing techniques with an emphasis on physiology and diagnostic applications, while the third section does the same for imaging modalities. Throughout the book, the authors rely on practical examples using real data from biomedical systems. They supply several programming examples in MATLAB® to provide hands-on experience and insight Integrating all major modalities and computational techniques in a single source, Biomedical Signal and Image Processing is a perfect introduction to the field as well as an ideal reference for the established professional.
Biomedical Signal And Image Processing Second Edition
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Author : Kayvan Najarian
language : en
Publisher: CRC Press
Release Date : 2012-05-04
Biomedical Signal And Image Processing Second Edition written by Kayvan Najarian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-04 with Medical categories.
First published in 2005, Biomedical Signal and Image Processing received wide and welcome reception from universities and industry research institutions alike, offering detailed, yet accessible information at the reference, upper undergraduate, and first year graduate level. Retaining all of the quality and precision of the first edition, Biomedical Signal and Image Processing, Second Edition offers a number of revisions and improvements to provide the most up-to-date reference available on the fundamental signal and image processing techniques that are used to process biomedical information. Addressing the application of standard and novel processing techniques to some of today’s principle biomedical signals and images over three sections, the book begins with an introduction to digital signal and image processing, including Fourier transform, image filtering, edge detection, and wavelet transform. The second section investigates specifically biomedical signals, such as ECG, EEG, and EMG, while the third focuses on imaging using CT, X-Ray, MRI, ultrasound, positron, and other biomedical imaging techniques. Updated and expanded, Biomedical Signal and Image Processing, Second Edition offers numerous additional, predominantly MATLAB, examples to all chapters to illustrate the concepts described in the text and ensure a complete understanding of the material. The author takes great care to clarify ambiguities in some mathematical equations and to further explain and justify the more complex signal and image processing concepts to offer a complete and understandable approach to complicated concepts.
Biomedical Signal And Image Processing
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Author : Mr. Rohit Manglik
language : en
Publisher: EduGorilla Publication
Release Date : 2023-06-23
Biomedical Signal And Image Processing written by Mr. Rohit Manglik and has been published by EduGorilla Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-23 with Technology & Engineering categories.
Covers techniques for analyzing biomedical signals and images, focusing on signal processing, imaging systems, and diagnostics in healthcare.
Biomedical Signal Processing
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Author : Ganesh R. Naik
language : en
Publisher: CRC Press
Release Date : 2023-09-27
Biomedical Signal Processing written by Ganesh R. Naik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-27 with Technology & Engineering categories.
This book presents the theoretical basis and applications of biomedical signal analysis and processing. Initially, the nature of the most common biomedical signals, such as electroencephalography, electromyography, electrocardiography and others, is described. The theoretical basis of linear signal processing is summarized, with continuous and discrete representation, linear filters and convolutions, Fourier and Wavelets transforms. Machine learning concepts are also presented, from classic methods to deep neural networks. Finally, several applications in neuroscience are presented and discussed, involving diagnosis and therapy, in addition to other applications. Features: Explains signal processing of neuroscience applications using modern data science techniques. Provides comprehensible review on biomedical signals nature and acquisition aspects. Focusses on selected applications of neurosciences, cardiovascular and muscle-related biomedical areas. Includes computational intelligence, machine learning and biomedical signal processing and analysis. Reviews theoretical basis of deep learning and state-of-the-art biomedical signal processing and analysis. This book is aimed at researchers, graduate students in biomedical signal processing, signal processing, electrical engineering, neuroscience and computer science.
Classification In Bioapps
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Author : Nilanjan Dey
language : en
Publisher: Springer
Release Date : 2017-11-10
Classification In Bioapps written by Nilanjan Dey and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-10 with Technology & Engineering categories.
This book on classification in biomedical image applications presents original and valuable research work on advances in this field, which covers the taxonomy of both supervised and unsupervised models, standards, algorithms, applications and challenges. Further, the book highlights recent scientific research on artificial neural networks in biomedical applications, addressing the fundamentals of artificial neural networks, support vector machines and other advanced classifiers, as well as their design and optimization. In addition to exploring recent endeavours in the multidisciplinary domain of sensors, the book introduces readers to basic definitions and features, signal filters and processing, biomedical sensors and automation of biomeasurement systems. The target audience includes researchers and students at engineering and medical schools, researchers and engineers in the biomedical industry, medical doctors and healthcare professionals.
Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques
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Author : Abdulhamit Subasi
language : en
Publisher: Academic Press
Release Date : 2019-03-16
Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-16 with Medical categories.
Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. - Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction - Explains how to apply machine learning techniques to EEG, ECG and EMG signals - Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series
Machine Learning In Bio Signal Analysis And Diagnostic Imaging
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2018-11-30
Machine Learning In Bio Signal Analysis And Diagnostic Imaging written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Science categories.
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. - Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging - Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining - Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains
Fresh Biomedical Insights Unraveling Biomedical Signal Processing Using Modern Techniques
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-04-11
Fresh Biomedical Insights Unraveling Biomedical Signal Processing Using Modern Techniques written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-11 with Medical categories.
Delve into the captivating world of biomedical signal processing with this comprehensive guide, unlocking the hidden insights within physiological signals. Through an engaging journey of ten chapters, discover the fundamental principles and cutting-edge techniques that empower medical professionals to diagnose diseases, monitor patient health, and develop life-saving treatments. Explore the vast landscape of biomedical signal processing, from the intricate patterns of an electrocardiogram (ECG) to the subtle fluctuations of a brainwave. Learn how these signals hold a treasure trove of information about our physiological state and how processing them with sophisticated algorithms extracts meaningful features and patterns, providing a window into the inner workings of the human body. Witness the transformative applications of biomedical signal processing across a wide spectrum of healthcare domains. From cardiology and neurology to respiratory medicine and oncology, discover how signal processing techniques detect abnormalities, monitor disease progression, and tailor treatments to individual patients. Gain insights into personalized medicine, remote health monitoring, and the emerging trends shaping the future of healthcare. Navigate through the challenges of biomedical signal processing, including the vast data volumes and inherent noise in physiological signals. Explore robust and efficient algorithms capable of extracting meaningful information from complex and noisy data. Delve into the latest advancements in signal processing, such as artificial intelligence and machine learning, and their impact on improving healthcare outcomes. With its comprehensive coverage, engaging narrative, and accessible explanations, this book is an invaluable resource for students, researchers, and practitioners in biomedical engineering, medicine, and related fields. Join us on this enlightening journey through the world of biomedical signal processing and witness the remarkable impact it has on the future of medicine. If you like this book, write a review on google books!
Adaptive Processing Of Brain Signals
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Author : Saeid Sanei
language : en
Publisher: John Wiley & Sons
Release Date : 2013-05-28
Adaptive Processing Of Brain Signals written by Saeid Sanei and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-28 with Technology & Engineering categories.
In this book, the field of adaptive learning and processing is extended to arguably one of its most important contexts which is the understanding and analysis of brain signals. No attempt is made to comment on physiological aspects of brain activity; instead, signal processing methods are developed and used to assist clinical findings. Recent developments in detection, estimation and separation of diagnostic cues from different modality neuroimaging systems are discussed. These include constrained nonlinear signal processing techniques which incorporate sparsity, nonstationarity, multimodal data, and multiway techniques. Key features: Covers advanced and adaptive signal processing techniques for the processing of electroencephalography (EEG) and magneto-encephalography (MEG) signals, and their correlation to the corresponding functional magnetic resonance imaging (fMRI) Provides advanced tools for the detection, monitoring, separation, localising and understanding of functional, anatomical, and physiological abnormalities of the brain Puts a major emphasis on brain dynamics and how this can be evaluated for the assessment of brain activity in various states such as for brain-computer interfacing emotions and mental fatigue analysis Focuses on multimodal and multiway adaptive processing of brain signals, the new direction of brain signal research