Books in Image and video processing

11-20 of 76 results in All results

Cognitive Systems and Signal Processing in Image Processing

• 1st Edition
• November 28, 2021
• Yu-Dong Zhang + 1 more
• English
• Paperback 978-0-12-824410-4

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• eBook 978-0-323-86009-3

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Cognitive Systems and Signal Processing in Image Processing presents different frameworks and applications of cognitive signal processing methods in image processing. This book provides an overview of recent applications in image processing by cognitive signal processing methods in the context of Big Data and Cognitive AI. It presents the amalgamation of cognitive systems and signal processing in the context of image processing approaches in solving various real-word application domains. This book reports the latest progress in cognitive big data and sustainable computing. Various real-time case studies and implemented works are discussed for better understanding and more clarity to readers. The combined model of cognitive data intelligence with learning methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues for computer vision in real-time.

Cardiovascular and Coronary Artery Imaging

• 1st Edition
• November 24, 2021
• Ayman S. El-Baz + 1 more
• English
• Paperback 978-0-12-822706-0

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• eBook 978-0-12-822707-7

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Cardiovascular and Coronary Artery Imaging, Volume One covers state-of-the-art approaches for automated non-invasive systems in early cardiovascular disease diagnosis. The book includes several prominent imaging modalities, such as MRI, CT and PET technologies. A special emphasis is placed on automated imaging analysis techniques, which are important to biomedical imaging analysis of the cardiovascular system. This is a comprehensive, multi-contributed reference work that details the latest developments in spatial, temporal and functional cardiac imaging.

Handbook of Pediatric Brain Imaging

• 1st Edition
• Volume 2
• October 27, 2021
• Hao Huang + 1 more
• English
• Paperback 978-0-12-816633-8

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• eBook 978-0-12-816642-0

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Handbook of Pediatric Brain Imaging: Methods and Applications presents state-of-the-art research on pediatric brain image acquisition and analysis from a broad range of imaging modalities, including MRI, EEG and MEG. With rapidly developing methods and applications of MRI, this book strongly emphasizes pediatric brain MRI, elaborating on the sub-categories of structure MRI, diffusion MRI, functional MRI, perfusion MRI and other MRI methods. It integrates a pediatric brain imaging perspective into imaging acquisition and analysis methods, covering head motion, small brain sizes, small cerebral blood flow of neonates, dynamic cortical gyrification, white matter tract growth, and much more.

fMRI Neurofeedback

• 1st Edition
• October 8, 2021
• Michelle Hampson
• English
• Paperback 978-0-12-822421-2

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• eBook 978-0-12-822436-6

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fMRI Neurofeedback provides a perspective on how the field of functional magnetic resonance imaging (fMRI) neurofeedback has evolved, an introduction to state-of-the-art methods used for fMRI neurofeedback, a review of published neuroscientific and clinical applications, and a discussion of relevant ethical considerations. It gives a view of the ongoing research challenges throughout and provides guidance for researchers new to the field on the practical implementation and design of fMRI neurofeedback protocols. This book is designed to be accessible to all scientists and clinicians interested in conducting fMRI neurofeedback research, addressing the variety of different knowledge gaps that readers may have given their varied backgrounds and avoiding field-specific jargon. The book, therefore, will be suitable for engineers, computer scientists, neuroscientists, psychologists, and physicians working in fMRI neurofeedback.

Image Processing for Automated Diagnosis of Cardiac Diseases

• 1st Edition
• July 13, 2021
• Kalpana Chauhan + 1 more
• English
• Paperback 978-0-323-85064-3

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• eBook 978-0-323-85065-0

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Image Processing for Automated Diagnosis of Cardiac Diseases highlights current and emerging technologies for the automated diagnosis of cardiac diseases. It presents concepts and practical algorithms, including techniques for the automated diagnosis of organs in motion using image processing. This book is suitable for biomedical engineering researchers, engineers and scientists in research and development, and clinicians who want to learn more about and develop advanced concepts in image processing to overcome the challenges of automated diagnosis of heart disease.

Radiomics and Its Clinical Application

• 1st Edition
• June 3, 2021
• Jie Tian + 3 more
• English
• Paperback 978-0-12-818101-0

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• eBook 978-0-12-818102-7

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The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting. This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice.

Intelligent Image and Video Compression

• 2nd Edition
• April 7, 2021
• David Bull + 1 more
• English
• Paperback 978-0-12-820353-8

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• eBook 978-0-12-820354-5

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Intelligent Image and Video Compression: Communicating Pictures, Second Edition explains the requirements, analysis, design and application of a modern video coding system. It draws on the authors’ extensive academic and professional experience in this field to deliver a text that is algorithmically rigorous yet accessible, relevant to modern standards and practical. It builds on a thorough grounding in mathematical foundations and visual perception to demonstrate how modern image and video compression methods can be designed to meet the rate-quality performance levels demanded by today's applications and users, in the context of prevailing network constraints. "David Bull and Fan Zhang have written a timely and accessible book on the topic of image and video compression. Compression of visual signals is one of the great technological achievements of modern times, and has made possible the great successes of streaming and social media and digital cinema. Their book, Intelligent Image and Video Compression covers all the salient topics ranging over visual perception, information theory, bandpass transform theory, motion estimation and prediction, lossy and lossless compression, and of course the compression standards from MPEG (ranging from H.261 through the most modern H.266, or VVC) and the open standards VP9 and AV-1. The book is replete with clear explanations and figures, including color where appropriate, making it quite accessible and valuable to the advanced student as well as the expert practitioner. The book offers an excellent glossary and as a bonus, a set of tutorial problems. Highly recommended!” --Al Bovik

Intravascular Ultrasound

• 1st Edition
• June 6, 2020
• Simone Balocco
• English
• Paperback 978-0-12-818833-0

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• eBook 978-0-12-818834-7

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Intravascular Ultrasound: From Acquisition to Advanced Quantitative Analysis covers topics of the whole imaging pipeline, ranging from the definition of the clinical problem and image acquisition systems to image processing and analysis, including the assisted clinical-decision making procedures and treatment planning (stent deployment and follow up). Atherosclerosis, a disease of the vessel wall that produces vessel narrowing and obstruction, is the major cause of cardiovascular diseases, such as heart attack or stroke. This book covers all aspects of this imaging tool that allows for the visualization of internal vessel structures and the quantification and characterization of coronary plaque.

Advances in Computational Techniques for Biomedical Image Analysis

• 1st Edition
• May 28, 2020
• Deepika Koundal + 1 more
• English
• Paperback 978-0-12-820024-7

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• eBook 978-0-12-820411-5

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Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation. Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems.

Machine Learning

• 2nd Edition
• February 19, 2020
• Sergios Theodoridis
• English
• Hardback 978-0-12-818803-3

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• eBook 978-0-12-818804-0

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Machine Learning: A Bayesian and Optimization Perspective, 2nd edition, gives a unified perspective on machine learning by covering both pillars of supervised learning, namely regression and classification. The book starts with the basics, including mean square, least squares and maximum likelihood methods, ridge regression, Bayesian decision theory classification, logistic regression, and decision trees. It then progresses to more recent techniques, covering sparse modelling methods, learning in reproducing kernel Hilbert spaces and support vector machines, Bayesian inference with a focus on the EM algorithm and its approximate inference variational versions, Monte Carlo methods, probabilistic graphical models focusing on Bayesian networks, hidden Markov models and particle filtering. Dimensionality reduction and latent variables modelling are also considered in depth. This palette of techniques concludes with an extended chapter on neural networks and deep learning architectures. The book also covers the fundamentals of statistical parameter estimation, Wiener and Kalman filtering, convexity and convex optimization, including a chapter on stochastic approximation and the gradient descent family of algorithms, presenting related online learning techniques as well as concepts and algorithmic versions for distributed optimization. Focusing on the physical reasoning behind the mathematics, without sacrificing rigor, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. Most of the chapters include typical case studies and computer exercises, both in MATLAB and Python. The chapters are written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as courses on sparse modeling, deep learning, and probabilistic graphical models. New to this edition: Complete re-write of the chapter on Neural Networks and Deep Learning to reflect the latest advances since the 1st edition. The chapter, starting from the basic perceptron and feed-forward neural networks concepts, now presents an in depth treatment of deep networks, including recent optimization algorithms, batch normalization, regularization techniques such as the dropout method, convolutional neural networks, recurrent neural networks, attention mechanisms, adversarial examples and training, capsule networks and generative architectures, such as restricted Boltzman machines (RBMs), variational autoencoders and generative adversarial networks (GANs). Expanded treatment of Bayesian learning to include nonparametric Bayesian methods, with a focus on the Chinese restaurant and the Indian buffet processes.