Advertisement
| matlab in medical field: Image Processing with MATLAB Omer Demirkaya, Musa H. Asyali, Prasanna K. Sahoo, 2008-12-22 Image Processing with MATLAB: Applications in Medicine and Biology explains complex, theory-laden topics in image processing through examples and MATLAB algorithms. It describes classical as well emerging areas in image processing and analysis. Providing many unique MATLAB codes and functions throughout, the book covers the theory of probability an |
| matlab in medical field: Diagnostic Radiology Physics with MATLAB® Johan Helmenkamp, Robert Bujila, Gavin Poludniowski, 2020-11-23 Imaging modalities in radiology produce ever-increasing amounts of data which need to be displayed, optimized, analyzed and archived: a big data as well as an image processing problem. Computer programming skills are rarely emphasized during the education and training of medical physicists, meaning that many individuals enter the workplace without the ability to efficiently solve many real-world clinical problems. This book provides a foundation for the teaching and learning of programming for medical physicists and other professions in the field of Radiology and offers valuable content for novices and more experienced readers alike. It focuses on providing readers with practical skills on how to implement MATLAB® as an everyday tool, rather than on solving academic and abstract physics problems. Further, it recognizes that MATLAB is only one tool in a medical physicist’s toolkit and shows how it can be used as the glue to integrate other software and processes together. Yet, with great power comes great responsibility. The pitfalls to deploying your own software in a clinical environment are also clearly explained. This book is an ideal companion for all medical physicists and medical professionals looking to learn how to utilize MATLAB in their work. Features Encompasses a wide range of medical physics applications in diagnostic and interventional radiology Advances the skill of the reader by taking them through real-world practical examples and solutions with access to an online resource of example code The diverse examples of varying difficulty make the book suitable for readers from a variety of backgrounds and with different levels of programming experience. |
| matlab in medical field: Practical Biomedical Signal Analysis Using MATLAB® Katarzyn J. Blinowska, Jaroslaw Zygierewicz, 2011-09-12 Practical Biomedical Signal Analysis Using MATLAB® presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and different types of data. The first several chapters of the text describe signal analysis techniques—including the newest and most advanced methods—in an easy and accessible way. MATLAB routines are listed when available and freely available software is discussed where appropriate. The final chapter explores the application of the methods to a broad range of biomedical signals, highlighting problems encountered in practice. A unified overview of the field, this book explains how to properly use signal processing techniques for biomedical applications and avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods. |
| matlab in medical field: Digital Signal Processing for Medical Imaging Using Matlab E.S. Gopi, 2012-09-13 This book describes medical imaging systems, such as X-ray, Computed tomography, MRI, etc. from the point of view of digital signal processing. Readers will see techniques applied to medical imaging such as Radon transformation, image reconstruction, image rendering, image enhancement and restoration, and more. This book also outlines the physics behind medical imaging required to understand the techniques being described. The presentation is designed to be accessible to beginners who are doing research in DSP for medical imaging. Matlab programs and illustrations are used wherever possible to reinforce the concepts being discussed. |
| matlab in medical field: Clinical Radiotherapy Physics with MATLAB Pavel Dvorak, 2018-06-12 The first MATLAB® programming book written specifically for clinical radiotherapy medical physicists and medical physics trainees, this much-needed book teaches users how to create their own clinical applications using MATLAB®, as a complement to commercial software particularly when the latter does not cover specific local clinical needs. Chapters explore key radiotherapy areas such as handling volumes, 3D dose calculation, comparing dose distributions, reconstructing treatment plans and their summations, and automated tests for machine quality assurance. Readers will learn to independently analyse and process images, doses, structures, and other radiotherapy clinical data to deal with standard and non-standard situations in radiotherapy. This book will also significantly improve understanding of areas such as data nature, information content, DICOM RT standard, and data flow. It will be an invaluable reference for students of medical physics, in addition to clinical radiotherapy physicists and researchers working in radiotherapy. Features: Includes real clinical medical physics applications derived from actual clinical problems Provides commented MATLAB® scripts working with sample data and/or own data matching input requirements Promotes critical thinking and practical problem solving skills |
| matlab in medical field: Deep Learning for Medical Image Analysis S. Kevin Zhou, Hayit Greenspan, Dinggang Shen, 2017-01-18 Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache |
| matlab in medical field: Artificial Cilia Jaap den Toonder, Patrick Onck, 2013-05-31 Natural cilia are tiny hairs on cells which have generated and sensed fluid flow in biological systems for billions of years. Mimicking this action in artificial systems presents interesting opportunities for flow control in lab-on-a-chip devices. Research into this field began almost a decade ago, and this book presents the state-of-the-art in this rapidly developing field of research inspired by nature. Establishing a link between nature and technology is a major attraction to those entering the field, which encompasses materials, processing, fluid mechanics, fluid-structure interaction, and biomedical applications. Artificial Cilia will appeal to anyone working in these areas and presents beautiful examples of how a biological system can form the successful basis for research and technical applications. The editors have been pioneers in the field since establishing a major European project on artificial cilia in 2005, and they are joined by leading experts from across the globe in presenting a comprehensive digest of this exciting new technology. |
| matlab in medical field: Applied Medical Image Processing Wolfgang Birkfellner, 2016-04-19 A widely used, classroom-tested text, Applied Medical Image Processing: A Basic Course delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field. Avoiding excessive mathematical formalisms, the book presents key principles by implementing algorithms from scratch and usin |
| matlab in medical field: Condition Monitoring Algorithms in MATLAB® Adam Jablonski, 2021-01-20 This book offers the first comprehensive and practice-oriented guide to condition monitoring algorithms in MATLAB®. After a concise introduction to vibration theory and signal processing techniques, the attention is moved to the algorithms. Each signal processing algorithm is presented in depth, from the theory to the application, and including extensive explanations on how to use the corresponding toolbox in MATLAB®. In turn, the book introduces various techniques for synthetic signals generation, as well as vibration-based analysis techniques for large data sets. A practical guide on how to directly access data from industrial condition monitoring systems (CMS) using MATLAB® .NET Libraries is also included. Bridging between research and practice, this book offers an extensive guide on condition monitoring algorithms to both scholars and professionals. “Condition Monitoring Algorithms in MATLAB® is a great resource for anyone in the field of condition monitoring. It is a unique as it presents the theory, and a number of examples in Matlab®, which greatly improve the learning experience. It offers numerous examples of coding styles in Matlab, thus supporting graduate students and professionals writing their own codes. Dr. Eric Bechhoefer Founder and CEO of GPMS Developer of the Foresight MX Health and Usage Monitoring System |
| matlab in medical field: MATLAB Programming for Biomedical Engineers and Scientists Andrew P. King, Paul Aljabar, 2017-06-14 MATLAB Programming for Biomedical Engineers and Scientists provides an easy-to-learn introduction to the fundamentals of computer programming in MATLAB. This book explains the principles of good programming practice, while demonstrating how to write efficient and robust code that analyzes and visualizes biomedical data. Aimed at the biomedical engineer, biomedical scientist, and medical researcher with little or no computer programming experience, it is an excellent resource for learning the principles and practice of computer programming using MATLAB. This book enables the reader to: - Analyze problems and apply structured design methods to produce elegant, efficient and well-structured program designs - Implement a structured program design in MATLAB, making good use of incremental development approaches - Write code that makes good use of MATLAB programming features, including control structures, functions and advanced data types - Write MATLAB code to read in medical data from files and write data to files - Write MATLAB code that is efficient and robust to errors in input data - Write MATLAB code to analyze and visualize medical data, including imaging data - Many real world biomedical problems and data show the practical application of programming concepts - Two whole chapters dedicated to the practicalities of designing and implementing more complex programs - An accompanying website containing freely available data and source code for the practical code examples, activities, and exercises in the book - For instructors, there are extra teaching materials including a complete set of slides, notes for a course based on the book, and course work suggestions |
| matlab in medical field: MATLAB for Behavioral Scientists David A. Rosenbaum, Jonathan Vaughan, Brad Wyble, 2014-07-17 Written specifically for those with no prior programming experience and minimal quantitative training, this accessible text walks behavioral science students and researchers through the process of programming using MATLAB. The book explores examples, terms, and programming needs relevant to those in the behavioral sciences and helps readers perform virtually any computational function in solving their research problems. Principles are illustrated with usable code. Each chapter opens with a list of objectives followed by new commands required to accomplish those goals. These objectives also serve as a reference to help readers easily relocate a section of interest. Sample code and output and chapter problems demonstrate how to write a program and explore a model so readers can see the results obtained using different equations and values. A web site provides solutions to selected problems and the book’s program code output and examples so readers can manipulate them as needed. The outputs on the website have color, motion, and sound. Highlights of the new edition include: •Updated to reflect changes in the most recent version of MATLAB, including special tricks and new functions. •More information on debugging and common errors and more basic problems in the rudiments of MATLAB to help novice users get up and running more quickly. •A new chapter on Psychtoolbox, a suite of programs specifically geared to behavioral science research. •A new chapter on Graphical User Interfaces (GUIs) for user-friendly communication. •Increased emphasis on pre-allocation of memory, recursion, handles, and matrix algebra operators. The book opens with an overview of what is to come and tips on how to write clear programs followed by pointers for interacting with MATLAB, including its commands and how to read error messages. The matrices chapter reviews how to store and access data. Chapter 4 examines how to carry out calculations followed by a review of how to perform various actions depending on the conditions. The chapter on input and output demonstrates how to design programs to create dialogs with users (e.g., participants in studies) and read and write data to and from external files. Chapter 7 reviews the data types available in MATLAB. Readers learn how to write a program as a stand-alone module in Chapter 8. In Chapters 9 and 10 readers learn how to create line and bar graphs or reshape images. Readers learn how to create animations and sounds in Chapter 11. The book concludes with tips on how to use MATLAB with applications such as GUIs and Psychtoolbox. Intended as a primary text for Matlab courses for advanced undergraduate and/or graduate students in experimental and cognitive psychology and/or neuroscience as well as a supplementary text for labs in data (statistical) analysis, research methods, and computational modeling (programming), the book also appeals to individual researchers in these disciplines who wish to get up and running in MATLAB. |
| matlab in medical field: MATLAB for Neuroscientists Pascal Wallisch, Michael E. Lusignan, Marc D. Benayoun, Tanya I. Baker, Adam Seth Dickey, Nicholas G. Hatsopoulos, 2014-01-09 MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners. - The first complete volume on MATLAB focusing on neuroscience and psychology applications - Problem-based approach with many examples from neuroscience and cognitive psychology using real data - Illustrated in full color throughout - Careful tutorial approach, by authors who are award-winning educators with strong teaching experience |
| matlab in medical field: PPG Signal Analysis Mohamed Elgendi, 2020-12-14 This book serves as a current resource for Photoplethysmogram (PPG) signal analysis using MATLAB®. This technology is critical in the evaluation of medical and diagnostic data utilized in mobile devices. Information and methodologies outlined in the text can be used to learn the empirical and experimental process (including data collection, data analysis, feature extractions, and more) from inception to conclusion. This book also discusses how introduced methodologies can be used and applied as tools that will teach the user how to validate, test, and simulate developed algorithms before implementing and deploying the algorithms on wearable, battery-driven, or point-of-care devices. |
| matlab in medical field: World Congress on Medical Physics and Biomedical Engineering September 7 - 12, 2009 Munich, Germany Olaf Dössel, Wolfgang C. Schlegel, 2010-01-06 Present Your Research to the World! The World Congress 2009 on Medical Physics and Biomedical Engineering – the triennial scientific meeting of the IUPESM - is the world’s leading forum for presenting the results of current scientific work in health-related physics and technologies to an international audience. With more than 2,800 presentations it will be the biggest conference in the fields of Medical Physics and Biomedical Engineering in 2009! Medical physics, biomedical engineering and bioengineering have been driving forces of innovation and progress in medicine and healthcare over the past two decades. As new key technologies arise with significant potential to open new options in diagnostics and therapeutics, it is a multidisciplinary task to evaluate their benefit for medicine and healthcare with respect to the quality of performance and therapeutic output. Covering key aspects such as information and communication technologies, micro- and nanosystems, optics and biotechnology, the congress will serve as an inter- and multidisciplinary platform that brings together people from basic research, R&D, industry and medical application to discuss these issues. As a major event for science, medicine and technology the congress provides a comprehensive overview and in–depth, first-hand information on new developments, advanced technologies and current and future applications. With this Final Program we would like to give you an overview of the dimension of the congress and invite you to join us in Munich! Olaf Dössel Congress President Wolfgang C. |
| matlab in medical field: MATLAB for Psychologists Mauro Borgo, Alessandro Soranzo, Massimo Grassi, 2012-03-24 The matrix laboratory interactive computing environment—MATLAB—has brought creativity to research in diverse disciplines, particularly in designing and programming experiments. More commonly used in mathematics and the sciences, it also lends itself to a variety of applications across the field of psychology. For the novice looking to use it in experimental psychology research, though, becoming familiar with MATLAB can be a daunting task. MATLAB for Psychologists expertly guides readers through the component steps, skills, and operations of the software, with plentiful graphics and examples to match the reader’s comfort level. Using an extended illustration, this concise volume explains the program’s usefulness at any point in an experiment, without the limits imposed by other types of software. And the authors demonstrate the responsiveness of MATLAB to the individual’s research needs, whether the task is programming experiments, creating sensory stimuli, running simulations, or calculating statistics for data analysis. Key features of the coverage: Thinking in a matrix way. Handling and plotting data. Guidelines for improved programming, sound, and imaging. Statistical analysis and signal detection theory indexes. The Graphical User Interface. The Psychophysics Toolbox. MATLAB for Psychologists serves a wide audience of advanced undergraduate and graduate level psychology students, professors, and researchers as well as lab technicians involved in programming psychology experiments. |
| matlab in medical field: Applications of MATLAB in Science and Engineering Tadeusz Michalowski, 2011-09-09 The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest. |
| matlab in medical field: Practical Image and Video Processing Using MATLAB Oge Marques, 2011-08-04 UP-TO-DATE, TECHNICALLY ACCURATE COVERAGE OF ESSENTIAL TOPICS IN IMAGE AND VIDEO PROCESSING This is the first book to combine image and video processing with a practical MATLAB®-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation. The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB® and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation. Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB®. Extra features of this book include: More than 30 MATLAB® tutorials, which consist of step-by-step guides toexploring image and video processing techniques using MATLAB® Chapters supported by figures, examples, illustrative problems, and exercises Useful websites and an extensive list of bibliographical references This accessible text is ideal for upper-level undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own. |
| matlab in medical field: Biomedical Image Analysis Recipes in MATLAB Constantino Carlos Reyes-Aldasoro, 2015-06-22 As its title suggests, this innovative book has been written for life scientists needing to analyse their data sets, and programmers, wanting a better understanding of the types of experimental images life scientists investigate on a regular basis. Each chapter presents one self-contained biomedical experiment to be analysed. Part I of the book presents its two basic ingredients: essential concepts of image analysis and Matlab. In Part II, algorithms and techniques are shown as series of recipes or solved examples that show how specific techniques are applied to a biomedical experiments like Western Blots, Histology, Scratch Wound Assays and Fluoresence. Each recipe begins with simple techniques that gradually advance in complexity. Part III presents some advanced techniques for the generation of publication quality figures. The book does not assume any computational or mathematical expertise. A practical, clearly-written introduction to biomedical image analysis that provides the tools for life scientists and engineers to use when solving problems in their own laboratories. Presents the basic concepts of MATLAB software and uses it throughout to show how it can execute flexible and powerful image analysis programs tailored to the specific needs of the problem. Within the context of four biomedical cases, it shows algorithms and techniques as series of recipes, or solved examples that show how a particular technique is applied in a specific experiment. Companion website containing example datasets, MATLAB files and figures from the book. |
| matlab in medical field: Digital Image Processing for Medical Applications Geoff Dougherty, 2009-04-09 Image processing is a hands-on discipline, and the best way to learn is by doing. This text takes its motivation from medical applications and uses real medical images and situations to illustrate and clarify concepts and to build intuition, insight and understanding. Designed for advanced undergraduates and graduate students who will become end-users of digital image processing, it covers the basics of the major clinical imaging modalities, explaining how the images are produced and acquired. It then presents the standard image processing operations, focusing on practical issues and problem solving. Crucially, the book explains when and why particular operations are done, and practical computer-based activities show how these operations affect real images. All images, links to the public-domain software ImageJ and custom plug-ins, and selected solutions are available from www.cambridge.org/books/dougherty. |
| matlab in medical field: Applied Optimization with MATLAB Programming P. Venkataraman, 2009-03-23 Technology/Engineering/Mechanical Provides all the tools needed to begin solving optimization problems using MATLAB® The Second Edition of Applied Optimization with MATLAB® Programming enables readers to harness all the features of MATLAB® to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems. This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB® tools. Two important new features of the text are: Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB® code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own. This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems. |
| matlab in medical field: Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques Abdulhamit Subasi, 2019-03-16 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 |
| matlab in medical field: Environmental Health Perspectives , 2007-08 |
| matlab in medical field: A Guide to MATLAB Brian R. Hunt, Ronald L. Lipsman, Jonathan M. Rosenberg, 2001-08-06 This book is a short, focused introduction to MATLAB and should be useful to both beginning and experienced users. |
| matlab in medical field: Translational Bioinformatics Applications in Healthcare Khalid Raza, Nilanjan Dey, 2021-04-20 Translational bioinformatics (TBI) involves development of storage, analytics, and advanced computational methods to harvest knowledge from voluminous biomedical and genomic data into 4P healthcare (proactive, predictive, preventive, and participatory). Translational Bioinformatics Applications in Healthcare offers a detailed overview on concepts of TBI, biological and clinical databases, clinical informatics, and pertinent real-case applications. It further illustrates recent advancements, tools, techniques, and applications of TBI in healthcare, including Internet of Things (IoT) potential, toxin databases, medical image analysis and telemedicine applications, analytics of COVID-19 CT images, viroinformatics and viral diseases, and COVID-19–related research. Covers recent technologies such as Blockchain, IoT, and Big data analytics in bioinformatics Presents the role of translational bioinformatic methods in the field of viroinformatics, as well as in drug development and repurposing Includes translational healthcare and NGS for clinical applications Illustrates translational medicine systems and their applications in better healthcare Explores medical image analysis with focus on CT images and novel coronavirus disease detection Aimed at researchers and graduate students in computational biology, data mining and knowledge discovery, algorithms and complexity, and interdisciplinary fields of studies, including bioinformatics, health-informatics, biostatistics, biomedical engineering, and viroinformatics. Khalid Raza is an Assistant Professor, the Department of Computer Science, Jamia Millia Islamia (Central University), New Delhi. His research interests include translational bioinformatics, computational intelligence methods and its applications in bioinformatics, viroinformatics, and health informatics. Nilanjan Dey is an Associate Professor, the Department of Computer Science and Engineering, JIS University, Kolkata, India. His research interests include medical imaging, machine learning, computer-aided diagnosis, and data mining. |
| matlab in medical field: Diagnostic Ultrasound Imaging: Inside Out Thomas L. Szabo, 2013-12-05 Diagnostic Ultrasound Imaging provides a unified description of the physical principles of ultrasound imaging, signal processing, systems and measurements. This comprehensive reference is a core resource for both graduate students and engineers in medical ultrasound research and design. With continuing rapid technological development of ultrasound in medical diagnosis, it is a critical subject for biomedical engineers, clinical and healthcare engineers and practitioners, medical physicists, and related professionals in the fields of signal and image processing. The book contains 17 new and updated chapters covering the fundamentals and latest advances in the area, and includes four appendices, 450 figures (60 available in color on the companion website), and almost 1,500 references. In addition to the continual influx of readers entering the field of ultrasound worldwide who need the broad grounding in the core technologies of ultrasound, this book provides those already working in these areas with clear and comprehensive expositions of these key new topics as well as introductions to state-of-the-art innovations in this field. - Enables practicing engineers, students and clinical professionals to understand the essential physics and signal processing techniques behind modern imaging systems as well as introducing the latest developments that will shape medical ultrasound in the future - Suitable for both newcomers and experienced readers, the practical, progressively organized applied approach is supported by hands-on MATLAB® code and worked examples that enable readers to understand the principles underlying diagnostic and therapeutic ultrasound - Covers the new important developments in the use of medical ultrasound: elastography and high-intensity therapeutic ultrasound. Many new developments are comprehensively reviewed and explained, including aberration correction, acoustic measurements, acoustic radiation force imaging, alternate imaging architectures, bioeffects: diagnostic to therapeutic, Fourier transform imaging, multimode imaging, plane wave compounding, research platforms, synthetic aperture, vector Doppler, transient shear wave elastography, ultrafast imaging and Doppler, functional ultrasound and viscoelastic models |
| matlab in medical field: MATLAB Kelly Bennett, 2014-09-08 MATLAB is an indispensable asset for scientists, researchers, and engineers. The richness of the MATLAB computational environment combined with an integrated development environment (IDE) and straightforward interface, toolkits, and simulation and modeling capabilities, creates a research and development tool that has no equal. From quick code prototyping to full blown deployable applications, MATLAB stands as a de facto development language and environment serving the technical needs of a wide range of users. As a collection of diverse applications, each book chapter presents a novel application and use of MATLAB for a specific result. |
| matlab in medical field: Analyzing Neural Time Series Data Mike X Cohen, 2014-01-17 A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings. This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman animals. It is the only book on the topic that covers both the theoretical background and the implementation in language that can be understood by readers without extensive formal training in mathematics, including cognitive scientists, neuroscientists, and psychologists. Readers who go through the book chapter by chapter and implement the examples in Matlab will develop an understanding of why and how analyses are performed, how to interpret results, what the methodological issues are, and how to perform single-subject-level and group-level analyses. Researchers who are familiar with using automated programs to perform advanced analyses will learn what happens when they click the “analyze now” button. The book provides sample data and downloadable Matlab code. Each of the 38 chapters covers one analysis topic, and these topics progress from simple to advanced. Most chapters conclude with exercises that further develop the material covered in the chapter. Many of the methods presented (including convolution, the Fourier transform, and Euler's formula) are fundamental and form the groundwork for other advanced data analysis methods. Readers who master the methods in the book will be well prepared to learn other approaches. |
| matlab in medical field: Signals and Systems Using MATLAB Luis F. Chaparro, Aydin Akan, 2018-10-29 Signals and Systems Using MATLAB, Third Edition, features a pedagogically rich and accessible approach to what can commonly be a mathematically dry subject. Historical notes and common mistakes combined with applications in controls, communications and signal processing help students understand and appreciate the usefulness of the techniques described in the text. This new edition features more end-of-chapter problems, new content on two-dimensional signal processing, and discussions on the state-of-the-art in signal processing. - Introduces both continuous and discrete systems early, then studies each (separately) in-depth - Contains an extensive set of worked examples and homework assignments, with applications for controls, communications, and signal processing - Begins with a review on all the background math necessary to study the subject - Includes MATLAB® applications in every chapter |
| matlab in medical field: Machine Learning for Healthcare Rashmi Agrawal, Jyotir Moy Chatterjee, Abhishek Kumar, Pramod Singh Rathore, Dac-Nhuong Le, 2020-12-08 Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them. Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector. The features of this book include: A unique and complete focus on applications of machine learning in the healthcare sector. An examination of how data analysis can be done using healthcare data and bioinformatics. An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors. |
| matlab in medical field: Artificial Intelligence and Its Applications Brahim Lejdel, Eliseo Clementini, Louai Alarabi, 2022-03-11 This book contains the proceedings of the second edition of the international Conference on Artificial Intelligence and its Applications (AIAP'21). This edition aims to bring together leading academic scientists, international researchers, and practitioners to exchange and share their experiences and research results on all aspects of Artificial Intelligence. It also provides an interdisciplinary platform for researchers, practitioners and students to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of Artificial Intelligence. This international conference offers an opportunity to bridge the gap between the Artificial Intelligence research community and people from the industry or working in other research areas including smart cities, big data, cloud computing, social networks, and energy. |
| matlab in medical field: Medical Anthropology Cecil G. Helman, 2023-01-30 This important volume includes key papers which outline the history, concepts, research findings and recent controversies in medical anthropology - the cross-cultural study of health, illness and medical care. Among the topics covered are transcultural psychiatry, food and nutrition, anthropology of the body, alcohol and drug use, traditional healers, childbirth and bereavement and the applications of medical anthropology to international health issues, such as the HIV/AIDS pandemic, malaria prevention and family planning. It is a valuable resource not only for scholars and students of medical anthropology but also for health professionals working in multi-cultural settings, or in international medical aid programmes. |
| matlab in medical field: Design and Fabrication of Diffractive Optical Elements with MATLAB Shanti Bhattacharya (Professor in Optics), Anand Vijayakumar, 2017 Given the many different applications and uses of diffractive optics, the importance of this field cannot be underestimated. This book supplements the available literature on diffractive optic elements (DOEs) by equipping readers with the skills to begin designing, simulating, and fabricating diffractive optics. The design of DOEs is presented with simple equations and step-by-step procedures for simulation--from the simplest 1D grating to the more complex multifunctional DOEs--and analyzing their diffraction patterns using MATLAB. The fundamentals of fabrication techniques such as photolithography, electron beam lithography, and focused ion beam lithography with basic instructions for the beginner are presented. Basic error analysis and error-correction techniques for a few cases are also discussed. The contents of all the chapters are supported throughout by practical exercises and clearly commented MATLAB® codes (the codes are also on an accompanying CD), making this book useful even to a novice programmer-- |
| matlab in medical field: Optics Using MATLAB Scott W. Teare, 2017 Provides a functional overview of the development of MATLAB code that can be used to enhance and increase one's understanding of optics though the use of visualization tools. The book ties a variety of optical topics to MATLAB programming activities and can act as a supplement to other textbooks or can stand alone. |
| matlab in medical field: Introduction to the Finite Element Method and Implementation with MATLAB® Gang Li, 2020-07-30 Connecting theory with numerical techniques using MATLAB®, this practical textbook equips students with the tools required to solve finite element problems. This hands-on guide covers a wide range of engineering problems through nine well-structured chapters including solid mechanics, heat transfer and fluid dynamics; equilibrium, steady state and transient; and 1-D, 2-D and 3-D problems. Engineering problems are discussed using case study examples, which are solved using a systematic approach, both by examining the steps manually and by implementing a complete MATLAB®code. This topical coverage is supplemented by discourse on meshing with a detailed explanation and implementation of 2-D meshing algorithms. Introducing theory and numerical techniques alongside comprehensive examples this text increases engagement and provides students with the confidence needed to implement their own computer codes to solve given problems. |
| matlab in medical field: Getting Started with MATLAB 7 Rudra Pratap, 2006 MATLAB is one of the most widely used tools in the field of engineering today. Its broad appeal lies in its interactive environment with hundreds of built-in functions. This book is designed to get you up and running in just a few hours. |
| matlab in medical field: Deep Learning Techniques for Biomedical and Health Informatics Sujata Dash, Biswa Ranjan Acharya, Mamta Mittal, Ajith Abraham, Arpad Kelemen, 2019-11-14 This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model. This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health. It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields. |
| matlab in medical field: Matlab Dorothy C. Attaway, 2013-06-03 MatLab, Third Edition is the only book that gives a full introduction to programming in MATLAB combined with an explanation of the software's powerful functions, enabling engineers to fully exploit its extensive capabilities in solving engineering problems. The book provides a systematic, step-by-step approach, building on concepts throughout the text, facilitating easier learning. Sections on common pitfalls and programming guidelines direct students towards best practice. The book is organized into 14 chapters, starting with programming concepts such as variables, assignments, input/output, and selection statements; moves onto loops; and then solves problems using both the 'programming concept' and the 'power of MATLAB' side-by-side. In-depth coverage is given to input/output, a topic that is fundamental to many engineering applications. Vectorized Code has been made into its own chapter, in order to emphasize the importance of using MATLAB efficiently. There are also expanded examples on low-level file input functions, Graphical User Interfaces, and use of MATLAB Version R2012b; modified and new end-of-chapter exercises; improved labeling of plots; and improved standards for variable names and documentation. This book will be a valuable resource for engineers learning to program and model in MATLAB, as well as for undergraduates in engineering and science taking a course that uses (or recommends) MATLAB. - Presents programming concepts and MATLAB built-in functions side-by-side - Systematic, step-by-step approach, building on concepts throughout the book, facilitating easier learning - Sections on common pitfalls and programming guidelines direct students towards best practice |
| matlab in medical field: Geoinformatics in Health Facility Analysis Praveen Kumar Rai, Mahendra Singh Nathawat, 2016-09-29 This book demonstrates how GIS techniques and statistical methods can be used to emphasise the characteristics of population and its related variables, vis-à-vis care facilities and the status of vector borne diseases, as well as for malaria modeling. Concentrating on the Varanasi district of India, the main aim of the book is to determine and map the density areas of vector borne diseases using GIS techniques. The book explores how health GIS is an important sub-discipline of health science and medical geography, which is traditionally focused on the spatial aspects of disease ecology and health care facility analysis. |
| matlab in medical field: Numerical Computing with MATLAB Cleve B. Moler, 2010-08-12 A revised textbook for introductory courses in numerical methods, MATLAB and technical computing, which emphasises the use of mathematical software. |
| matlab in medical field: American Journal of Public Health , 1998-07 |
MATLAB - MathWorks
MATLAB combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the …
MATLAB Online - MATLAB & Simulink - MathWorks
MATLAB Online provides access to MATLAB from any standard web browser wherever you have Internet access. MATLAB Online offers cloud storage and synchronization, and collaboration …
MathWorks - Maker of MATLAB and Simulink
MathWorks develops, sells, and supports MATLAB and Simulink products.
Get Started with MATLAB - MathWorks
MATLAB helps you take your ideas beyond the desktop. You can run your analyses on larger data sets, and scale up to clusters and clouds. MATLAB code can be integrated with other …
Programming with MATLAB - MATLAB & Simulink - MathWorks
MATLAB is a high-level programming language designed for engineers and scientists that expresses matrix and array mathematics directly. You can use MATLAB for everything, from …
Getting Started - MATLAB - MATLAB & Simulink - MathWorks
This video shows you the basics, giving you an idea of what working in MATLAB is like. Import data, define variables, and perform calculations using elements of the MATLAB desktop …
MATLAB for Students - MATLAB & Simulink - MathWorks
The suite includes MATLAB, Simulink, and 10 of the most widely used add-on products, as well as built-in support for prototyping, testing, and running models on low-cost target hardware. …
Download and Install MATLAB - MATLAB & Simulink
To install MATLAB, download the installer for your platform and MATLAB release from MathWorks Downloads. Then, run the installer and follow the prompts to complete the …
MATLAB Documentation - MathWorks
The matrix-based MATLAB language is the world’s most natural way to express computational mathematics. Built-in graphics make it easy to visualize and gain insights from data. The …
MATLAB Tutorials - MATLAB & Simulink - MathWorks
Get started using MATLAB quickly and for free. Explore interactive courses, documentation and code examples, how-to videos, and more.
MATLAB - MathWorks
MATLAB combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the …
MATLAB Online - MATLAB & Simulink - MathWorks
MATLAB Online provides access to MATLAB from any standard web browser wherever you have Internet access. MATLAB Online offers cloud storage and synchronization, and collaboration …
MathWorks - Maker of MATLAB and Simulink
MathWorks develops, sells, and supports MATLAB and Simulink products.
Get Started with MATLAB - MathWorks
MATLAB helps you take your ideas beyond the desktop. You can run your analyses on larger data sets, and scale up to clusters and clouds. MATLAB code can be integrated with other …
Programming with MATLAB - MATLAB & Simulink - MathWorks
MATLAB is a high-level programming language designed for engineers and scientists that expresses matrix and array mathematics directly. You can use MATLAB for everything, from …
Getting Started - MATLAB - MATLAB & Simulink - MathWorks
This video shows you the basics, giving you an idea of what working in MATLAB is like. Import data, define variables, and perform calculations using elements of the MATLAB desktop …
MATLAB for Students - MATLAB & Simulink - MathWorks
The suite includes MATLAB, Simulink, and 10 of the most widely used add-on products, as well as built-in support for prototyping, testing, and running models on low-cost target hardware. Buy …
Download and Install MATLAB - MATLAB & Simulink
To install MATLAB, download the installer for your platform and MATLAB release from MathWorks Downloads. Then, run the installer and follow the prompts to complete the installation. Then, …
MATLAB Documentation - MathWorks
The matrix-based MATLAB language is the world’s most natural way to express computational mathematics. Built-in graphics make it easy to visualize and gain insights from data. The …
MATLAB Tutorials - MATLAB & Simulink - MathWorks
Get started using MATLAB quickly and for free. Explore interactive courses, documentation and code examples, how-to videos, and more.
