Download or read book Advanced Image Processing in Magnetic Resonance Imaging written by Luigi Landini and published by CRC Press. This book was released on 2018-10-03 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: The popularity of magnetic resonance (MR) imaging in medicine is no mystery: it is non-invasive, it produces high quality structural and functional image data, and it is very versatile and flexible. Research into MR technology is advancing at a blistering pace, and modern engineers must keep up with the latest developments. This is only possible with a firm grounding in the basic principles of MR, and Advanced Image Processing in Magnetic Resonance Imaging solidly integrates this foundational knowledge with the latest advances in the field. Beginning with the basics of signal and image generation and reconstruction, the book covers in detail the signal processing techniques and algorithms, filtering techniques for MR images, quantitative analysis including image registration and integration of EEG and MEG techniques with MR, and MR spectroscopy techniques. The final section of the book explores functional MRI (fMRI) in detail, discussing fundamentals and advanced exploratory data analysis, Bayesian inference, and nonlinear analysis. Many of the results presented in the book are derived from the contributors' own work, imparting highly practical experience through experimental and numerical methods. Contributed by international experts at the forefront of the field, Advanced Image Processing in Magnetic Resonance Imaging is an indispensable guide for anyone interested in further advancing the technology and capabilities of MR imaging.

Download or read book Handbook of Medical Image Processing and Analysis written by Isaac Bankman and published by Elsevier. This book was released on 2008-12-24 with total page 1009 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Medical Image Processing and Analysis is a comprehensive compilation of concepts and techniques used for processing and analyzing medical images after they have been generated or digitized. The Handbook is organized into six sections that relate to the main functions: enhancement, segmentation, quantification, registration, visualization, and compression, storage and communication.The second edition is extensively revised and updated throughout, reflecting new technology and research, and includes new chapters on: higher order statistics for tissue segmentation; tumor growth modeling in oncological image analysis; analysis of cell nuclear features in fluorescence microscopy images; imaging and communication in medical and public health informatics; and dynamic mammogram retrieval from web-based image libraries.For those looking to explore advanced concepts and access essential information, this second edition of Handbook of Medical Image Processing and Analysis is an invaluable resource. It remains the most complete single volume reference for biomedical engineers, researchers, professionals and those working in medical imaging and medical image processing.Dr. Isaac N. Bankman is the supervisor of a group that specializes on imaging, laser and sensor systems, modeling, algorithms and testing at the Johns Hopkins University Applied Physics Laboratory. He received his BSc degree in Electrical Engineering from Bogazici University, Turkey, in 1977, the MSc degree in Electronics from University of Wales, Britain, in 1979, and a PhD in Biomedical Engineering from the Israel Institute of Technology, Israel, in 1985. He is a member of SPIE. - Includes contributions from internationally renowned authors from leading institutions - NEW! 35 of 56 chapters have been revised and updated. Additionally, five new chapters have been added on important topics incluling Nonlinear 3D Boundary Detection, Adaptive Algorithms for Cancer Cytological Diagnosis, Dynamic Mammogram Retrieval from Web-Based Image Libraries, Imaging and Communication in Health Informatics and Tumor Growth Modeling in Oncological Image Analysis. - Provides a complete collection of algorithms in computer processing of medical images - Contains over 60 pages of stunning, four-color images

Download or read book High Performance Medical Image Processing written by Sanjay Saxena and published by CRC Press. This book was released on 2022-07-07 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: The processing of medical images in a reasonable timeframe and with high definition is very challenging. This volume helps to meet that challenge by presenting a thorough overview of medical imaging modalities, its processing, high-performance computing, and the need to embed parallelism in medical image processing techniques to achieve efficient and fast results. With contributions from researchers from prestigious laboratories and educational institutions, High-Performance Medical Image Processing provides important information on medical image processing techniques, parallel computing techniques, and embedding parallelism in different image processing techniques. A comprehensive review of parallel algorithms in medical image processing problems is a key feature of this book. The volume presents the relevant theoretical frameworks and the latest empirical research findings in the area and provides detailed descriptions about the diverse high-performance techniques. Topics discussed include parallel computing, multicore architectures and their applications in image processing, machine learning applications, conventional and advanced magnetic resonance imaging methods, hyperspectral image processing, algorithms for segmenting 2D slices for 3D viewing, and more. Case studies, such as on the detection of cancer tumors, expound on the information presented. Key features: Provides descriptions of different medical imaging modalities and their applications Discusses the basics and advanced aspects of parallel computing with different multicore architectures Expounds on the need for embedding data and task parallelism in different medical image processing techniques Presents helpful examples and case studies of the discussed methods This book will be valuable for professionals, researchers, and students working in the field of healthcare engineering, medical imaging technology, applications in machine and deep learning, and more. It is also appropriate for courses in computer engineering, biomedical engineering and electrical engineering based on artificial intelligence, parallel computing, high performance computing, and machine learning and its applications in medical imaging.

Download or read book Advanced Biomedical Image Analysis written by Mark Haidekker and published by John Wiley & Sons. This book was released on 2011-03-29 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive reference of cutting-edge advanced techniques for quantitative image processing and analysis Medical diagnostics and intervention, and biomedical research rely progressively on imaging techniques, namely, the ability to capture, store, analyze, and display images at the organ, tissue, cellular, and molecular level. These tasks are supported by increasingly powerful computer methods to process and analyze images. This text serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on biomedical applications. It offers both theory and practical examples for immediate application of the topics as well as for in-depth study. Advanced Biomedical Image Analysis presents methods in the four major areas of image processing: image enhancement and restoration, image segmentation, image quantification and classification, and image visualization. In each instance, the theory, mathematical foundation, and basic description of an image processing operator is provided, as well as a discussion of performance features, advantages, and limitations. Key algorithms are provided in pseudo-code to help with implementation, and biomedical examples are included in each chapter. Image registration, storage, transport, and compression are also covered, and there is a review of image analysis and visualization software. Members of the academic community involved in image-related research as well as members of the professional R&D sector will rely on this volume. It is also well suited as a textbook for graduate-level image processing classes in the computer science and engineering fields.

Download or read book Principles And Advanced Methods In Medical Imaging And Image Analysis written by Atam P Dhawan and published by World Scientific. This book was released on 2008-03-17 with total page 869 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computerized medical imaging and image analysis have been the central focus in diagnostic radiology. They provide revolutionalizing tools for the visualization of physiology as well as the understanding and quantitative measurement of physiological parameters. This book offers in-depth knowledge of medical imaging instrumentation and techniques as well as multidimensional image analysis and classification methods for research, education, and applications in computer-aided diagnostic radiology. Internationally renowned researchers and experts in their respective areas provide detailed descriptions of the basic foundation as well as the most recent developments in medical imaging, thus helping readers to understand theoretical and advanced concepts for important research and clinical applications.

Download or read book Principles and Advanced Methods in Medical Imaging and Image Analysis written by Atam P. Dhawan and published by World Scientific. This book was released on 2008 with total page 869 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computerized medical imaging and image analysis have been the central focus in diagnostic radiology. They provide revolutionalizing tools for the visualization of physiology as well as the understanding and quantitative measurement of physiological parameters. This book offers in-depth knowledge of medical imaging instrumentation and techniques as well as multidimensional image analysis and classification methods for research, education, and applications in computer-aided diagnostic radiology. Internationally renowned researchers and experts in their respective areas provide detailed descriptions of the basic foundation as well as the most recent developments in medical imaging, thus helping readers to understand theoretical and advanced concepts for important research and clinical applications. Sample Chapter(s). Sample Chapter(s). Chapter 1: Introduction to Medical Imaging and Image Analysis: A Multidisciplinary Paradigm (60 KB). Contents: Principles of Medical Imaging and Image Analysis; Recent Advances in Medical Imaging and Image Analysis; Medical Imaging Applications, Case Studies and Future Trends. Readership: Graduate-level readers in medical imaging and medical image processing.

Download or read book Advanced Image Processing in Cardiac Magnetic Resonance Imaging with Application in Myocardial Perfusion Quantification written by Matthew James Jacobs and published by . This book was released on 2017 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cardiac magnetic resonance imaging (CMRI) has been proven to be a valuable source of diagnostic information concerning heart health. One application, myocardial blood flow (MBF) quantification using first-pass contrast-enhanced myocardial perfusion, has aided the detection of coronary artery disease and provides an accurate evaluation of myocardial ischemia, an identifier of coronary artery stenosis. However, the image processing and analysis requires tedious user interaction, increasing the time and effort required to utilize it. In addition, it can introduce subjectivity and variability into the data analysis, which further limits the potential use of the modality. This dissertation presents several automated image processing algorithms to increase the accuracy, consistency, and efficiency of CMR image processing, and validates them on large, clinical datasets. First, an automated method is proposed to measure the arterial input function (AIF) from the left ventricle (LV), which is required for the accurate quantification of MBF. The proposed algorithm consists of several automated image processing steps including motion correction, intensity correction, detection of the LV, independent component analysis, and LV pixel thresholding to calculate the AIF signal. The method was validated in 270 clinical studies by comparing automated results to manual reference measurements using several quality metrics. Additionally, the MBF was calculated and compared in a subset of 21 clinical studies from healthy volunteers using the automated and manual AIF measurements. The proposed method successfully processed 99.63% of the image series. Manual and automatic AIF measurement showed strong agreement, and the automated method effectively selected bright LV pixels, excluded papillary muscles, and required much less processing time than the manual approach. No significant difference was found in MBF estimates between manually and automatically measured AIFs. Second, this dissertation presents an automated method for segmenting the myocardium from MBF maps, making segmental analysis faster and easier to achieve. The proposed method employs active contours for myocardial segmentation, and landmark detection for the anchoring of sector-wise analysis. These methods were validated in a group of 91 clinical perfusion studies against a manual reference standard. The proposed method processed 100% of the studies successfully and results agreed with the manual reference standard, both in terms of segmented area and measurements from sector-wise analysis. Together, these automated methods form a fully automatic MBF quantification pipeline for first-pass contrast-enhanced myocardial perfusion imaging. These advancements make the modality more readily available and applicable to a larger number of patients and centers throughout the field.

Download or read book Principles of Magnetic Resonance Imaging written by Zhi-Pei Liang and published by Wiley-IEEE Press. This book was released on 2000 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 1971 Dr. Paul C. Lauterbur pioneered spatial information encoding principles that made image formation possible by using magnetic resonance signals. Now Lauterbur, "father of the MRI", and Dr. Zhi-Pei Liang have co-authored the first engineering textbook on magnetic resonance imaging. This long-awaited, definitive text will help undergraduate and graduate students of biomedical engineering, biomedical imaging scientists, radiologists, and electrical engineers gain an in-depth understanding of MRI principles. The authors use a signal processing approach to describe the fundamentals of magnetic resonance imaging. You will find a clear and rigorous discussion of these carefully selected essential topics: Mathematical fundamentals Signal generation and detection principles Signal characteristics Signal localization principles Image reconstruction techniques Image contrast mechanisms Image resolution, noise, and artifacts Fast-scan imaging Constrained reconstruction Complete with a comprehensive set of examples and homework problems, Principles of Magnetic Resonance Imaging is the must-read book to improve your knowledge of this revolutionary technique.

Download or read book Image Processing in Radiology written by Emanuele Neri and published by Springer Science & Business Media. This book was released on 2007-12-31 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, written by leading experts from many countries, provides a comprehensive and up-to-date description of how to use 2D and 3D processing tools in clinical radiology. The opening section covers a wide range of technical aspects. In the main section, the principal clinical applications are described and discussed in depth. A third section focuses on a variety of special topics. This book will be invaluable to radiologists of any subspecialty.

Download or read book Improved Signal and Image Interpolation in Biomedical Applications The Case of Magnetic Resonance Imaging MRI written by Ciulla, Carlo and published by IGI Global. This book was released on 2009-03-31 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents novel concepts supported through mathematics to create unique theories related to interpolation"--Provided by publisher.

Download or read book Signal Processing for Magnetic Resonance Imaging and Spectroscopy written by Hong Yan and published by CRC Press. This book was released on 2002-02-20 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reference/text contains the latest signal processing techniques in magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) for more efficient clinical diagnoses-providing ready-to-use algorithms for image segmentation and analysis, reconstruction and visualization, and removal of distortions and artifacts for increased detec

Download or read book Medical Image Processing written by Geoff Dougherty and published by Springer Science & Business Media. This book was released on 2011-07-25 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is designed for end users in the field of digital imaging, who wish to update their skills and understanding with the latest techniques in image analysis. The book emphasizes the conceptual framework of image analysis and the effective use of image processing tools. It uses applications in a variety of fields to demonstrate and consolidate both specific and general concepts, and to build intuition, insight and understanding. Although the chapters are essentially self-contained they reference other chapters to form an integrated whole. Each chapter employs a pedagogical approach to ensure conceptual learning before introducing specific techniques and “tricks of the trade”. The book concentrates on a number of current research applications, and will present a detailed approach to each while emphasizing the applicability of techniques to other problems. The field of topics is wide, ranging from compressive (non-uniform) sampling in MRI, through automated retinal vessel analysis to 3-D ultrasound imaging and more. The book is amply illustrated with figures and applicable medical images. The reader will learn the techniques which experts in the field are currently employing and testing to solve particular research problems, and how they may be applied to other problems.

Download or read book Quantitative Magnetic Resonance Imaging written by Nicole Seiberlich and published by Academic Press. This book was released on 2020-11-18 with total page 1094 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative Magnetic Resonance Imaging is a 'go-to' reference for methods and applications of quantitative magnetic resonance imaging, with specific sections on Relaxometry, Perfusion, and Diffusion. Each section will start with an explanation of the basic techniques for mapping the tissue property in question, including a description of the challenges that arise when using these basic approaches. For properties which can be measured in multiple ways, each of these basic methods will be described in separate chapters. Following the basics, a chapter in each section presents more advanced and recently proposed techniques for quantitative tissue property mapping, with a concluding chapter on clinical applications. The reader will learn: - The basic physics behind tissue property mapping - How to implement basic pulse sequences for the quantitative measurement of tissue properties - The strengths and limitations to the basic and more rapid methods for mapping the magnetic relaxation properties T1, T2, and T2* - The pros and cons for different approaches to mapping perfusion - The methods of Diffusion-weighted imaging and how this approach can be used to generate diffusion tensor - maps and more complex representations of diffusion - How flow, magneto-electric tissue property, fat fraction, exchange, elastography, and temperature mapping are performed - How fast imaging approaches including parallel imaging, compressed sensing, and Magnetic Resonance - Fingerprinting can be used to accelerate or improve tissue property mapping schemes - How tissue property mapping is used clinically in different organs - Structured to cater for MRI researchers and graduate students with a wide variety of backgrounds - Explains basic methods for quantitatively measuring tissue properties with MRI - including T1, T2, perfusion, diffusion, fat and iron fraction, elastography, flow, susceptibility - enabling the implementation of pulse sequences to perform measurements - Shows the limitations of the techniques and explains the challenges to the clinical adoption of these traditional methods, presenting the latest research in rapid quantitative imaging which has the possibility to tackle these challenges - Each section contains a chapter explaining the basics of novel ideas for quantitative mapping, such as compressed sensing and Magnetic Resonance Fingerprinting-based approaches

Download or read book Functional Magnetic Resonance Imaging Processing written by Xingfeng Li and published by Springer Science & Business Media. This book was released on 2013-09-14 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: With strong numerical and computational focus, this book serves as an essential resource on the methods for functional neuroimaging analysis, diffusion weighted image analysis, and longitudinal VBM analysis. It includes four MRI image modalities analysis methods. The first covers the PWI methods, which is the basis for understanding cerebral flow in human brain. The second part, the book’s core, covers fMRI methods in three specific domains: first level analysis, second level analysis, and effective connectivity study. The third part covers the analysis of Diffusion weighted image, i.e. DTI, QBI and DSI image analysis. Finally, the book covers (longitudinal) VBM methods and its application to Alzheimer’s disease study.

Download or read book Advanced Imaging in Biology and Medicine written by Ch.W. Sensen and published by Springer Science & Business Media. This book was released on 2008-12-03 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: A picture says more than a thousand words. This is something that we all know to be true. Imaging has been important since the early days of medicine and bi- ogy, as seen in the anatomical studies of Leonardo Da Vinci or Andreas Vesalius. More than 100 years ago, the ?rst noninvasive imaging technologies, such as K- rad Roentgen’s X-ray technology,were applied to the medical ?eld—and while still crude—revolutionized medical diagnosis. Today, every patient will be exposed to some kind of advanced imaging technology such as medical resonance imaging, computed tomography or four-dimensional ultrasound during their lifetime. Many diseases, such as brain tumors, are initially diagnosed solely by imaging, and most of the surgical planning relies on the patient imagery. 4D ultrasound is available to expecting parents who wish to create unique early memories of the new baby, and it may soon be used for the morphometric diagnosis of malformations that may one day be treatable—inutero! Light and electron microscopy are unequal brethren, which have contributed to most of our knowledge about the existence and organization of cells, tissues and microorganisms. Every student of biology or medicine is introduced to the fascinating images of the microcosm. New advances have converted these im- ing technologies, which were considered by many to be antiquated, into powerful tools for research in systems biology and related ?elds.

Download or read book Machine Learning and Medical Imaging written by Guorong Wu and published by Academic Press. This book was released on 2016-08-11 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. - Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems - Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics - Features self-contained chapters with a thorough literature review - Assesses the development of future machine learning techniques and the further application of existing techniques

Download or read book Compressed Sensing for Magnetic Resonance Image Reconstruction written by Angshul Majumdar and published by Cambridge University Press. This book was released on 2015-02-26 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expecting the reader to have some basic training in liner algebra and optimization, the book begins with a general discussion on CS techniques and algorithms. It moves on to discussing single channel static MRI, the most common modality in clinical studies. It then takes up multi-channel MRI and the interesting challenges consequently thrown up in signal reconstruction. Off-line and on-line techniques in dynamic MRI reconstruction are visited. Towards the end the book broadens the subject by discussing how CS is being applied to other areas of biomedical signal processing like X-ray, CT and EEG acquisition. The emphasis throughout is on qualitative understanding of the subject rather than on quantitative aspects of mathematical forms. The book is intended for MRI engineers interested in the brass tacks of image formation; medical physicists interested in advanced techniques in image reconstruction; and mathematicians or signal processing engineers.