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Medical Image Analysis Methods
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Book Synopsis Guide to Medical Image Analysis by : Klaus D. Toennies
Download or read book Guide to Medical Image Analysis written by Klaus D. Toennies and published by Springer. This book was released on 2017-03-29 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive guide provides a uniquely practical, application-focused introduction to medical image analysis. This fully updated new edition has been enhanced with material on the latest developments in the field, whilst retaining the original focus on segmentation, classification and registration. Topics and features: presents learning objectives, exercises and concluding remarks in each chapter; describes a range of common imaging techniques, reconstruction techniques and image artifacts, and discusses the archival and transfer of images; reviews an expanded selection of techniques for image enhancement, feature detection, feature generation, segmentation, registration, and validation; examines analysis methods in view of image-based guidance in the operating room (NEW); discusses the use of deep convolutional networks for segmentation and labeling tasks (NEW); includes appendices on Markov random field optimization, variational calculus and principal component analysis.
Book Synopsis Medical Image Analysis Methods by : Lena Costaridou
Download or read book Medical Image Analysis Methods written by Lena Costaridou and published by CRC Press. This book was released on 2005-07-13 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: To successfully detect and diagnose disease, it is vital for medical diagnosticians to properly apply the latest medical imaging technologies. It is a worrisome reality that due to either the nature or volume of some of the images provided, early or obscured signs of disease can go undetected or be misdiagnosed. To combat these inaccuracies, diagno
Book Synopsis Medical Image Processing by : Geoff Dougherty
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.
Book Synopsis Introduction to Medical Image Analysis by : Rasmus R. Paulsen
Download or read book Introduction to Medical Image Analysis written by Rasmus R. Paulsen and published by Springer Nature. This book was released on 2020-05-26 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-follow textbook presents an engaging introduction to the fascinating world of medical image analysis. Avoiding an overly mathematical treatment, the text focuses on intuitive explanations, illustrating the key algorithms and concepts in a way which will make sense to students from a broad range of different backgrounds. Topics and features: explains what light is, and how it can be captured by a camera and converted into an image, as well as how images can be compressed and stored; describes basic image manipulation methods for understanding and improving image quality, and a useful segmentation algorithm; reviews the basic image processing methods for segmenting or enhancing certain features in an image, with a focus on morphology methods for binary images; examines how to detect, describe, and recognize objects in an image, and how the nature of color can be used for segmenting objects; introduces a statistical method to determine what class of object the pixels in an image represent; describes how to change the geometry within an image, how to align two images so that they are as similar as possible, and how to detect lines and paths in images; provides further exercises and other supplementary material at an associated website. This concise and accessible textbook will be invaluable to undergraduate students of computer science, engineering, medicine, and any multi-disciplinary courses that combine topics on health with data science. Medical practitioners working with medical imaging devices will also appreciate this easy-to-understand explanation of the technology.
Book Synopsis Principles and Advanced Methods in Medical Imaging and Image Analysis by :
Download or read book Principles and Advanced Methods in Medical Imaging and Image Analysis written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis by : Nilanjan Dey
Download or read book Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis written by Nilanjan Dey and published by Academic Press. This book was released on 2019-07-31 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images. Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications Introduces several techniques for medical image processing and analysis for CAD systems design
Book Synopsis Deep Learning for Medical Image Analysis by : S. Kevin Zhou
Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2023-12-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is 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 are applied to medical image detection, segmentation, registration, and computer-aided analysis. · Covers common research problems in medical image analysis and their challenges · Describes the latest 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 cardiac, neural and functional, colonoscopy, OCTA applications and model assessment · Includes a Foreword written by Nicholas Ayache
Book Synopsis Medical Image Analysis by : Alejandro Frangi
Download or read book Medical Image Analysis written by Alejandro Frangi and published by Academic Press. This book was released on 2023-09-20 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC. Provides an authoritative description of key concepts and methods Includes tutorial-based sections that clearly explain principles and their application to different medical domains Presents a representative selection of topics to match a modern and relevant approach to medical image computing
Book Synopsis Biomedical Image Analysis by : Aly A. Farag
Download or read book Biomedical Image Analysis written by Aly A. Farag and published by . This book was released on 2014 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ideal for classroom use and self-study, this book explains the implementation of the most effective modern methods in image analysis, covering segmentation, registration and visualisation, and focusing on the key theories, algorithms and applications that have emerged from recent progress in computer vision, imaging and computational biomedical science. Structured around five core building blocks - signals, systems, image formation and modality; stochastic models; computational geometry; level set methods; and tools and CAD models - it provides a solid overview of the field. Mathematical and statistical topics are presented in a straightforward manner, enabling the reader to gain a deep understanding of the subject without becoming entangled in mathematical complexities. Theory is connected to practical examples in x-ray, ultrasound, nuclear medicine, MRI and CT imaging, removing the abstract nature of the models and assisting reader understanding, whilst computer simulations, online course slides and a solution manual provide a complete instructor package.
Book Synopsis Machine Learning and Medical Imaging by : Guorong Wu
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 512 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
Book Synopsis Advances in Computational Techniques for Biomedical Image Analysis by : Deepika Koundal
Download or read book Advances in Computational Techniques for Biomedical Image Analysis written by Deepika Koundal and published by Academic Press. This book was released on 2020-05-28 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Covers various challenges and common research issues related to biomedical image analysis Describes advanced computational approaches for biomedical image analysis Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization Explores cloud based medical imaging together with medical imaging security and forensics
Book Synopsis Color Medical Image Analysis by : M. Emre Celebi
Download or read book Color Medical Image Analysis written by M. Emre Celebi and published by Springer Science & Business Media. This book was released on 2012-09-16 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images. The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.
Book Synopsis Pattern Recognition and Signal Analysis in Medical Imaging by : Anke Meyer-Baese
Download or read book Pattern Recognition and Signal Analysis in Medical Imaging written by Anke Meyer-Baese and published by Elsevier. This book was released on 2014-03-21 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical imaging is one of the heaviest funded biomedical engineering research areas. The second edition of Pattern Recognition and Signal Analysis in Medical Imaging brings sharp focus to the development of integrated systems for use in the clinical sector, enabling both imaging and the automatic assessment of the resultant data. Since the first edition, there has been tremendous development of new, powerful technologies for detecting, storing, transmitting, analyzing, and displaying medical images. Computer-aided analytical techniques, coupled with a continuing need to derive more information from medical images, has led to a growing application of digital processing techniques in cancer detection as well as elsewhere in medicine. This book is an essential tool for students and professionals, compiling and explaining proven and cutting-edge methods in pattern recognition for medical imaging. New edition has been expanded to cover signal analysis, which was only superficially covered in the first edition New chapters cover Cluster Validity Techniques, Computer-Aided Diagnosis Systems in Breast MRI, Spatio-Temporal Models in Functional, Contrast-Enhanced and Perfusion Cardiovascular MRI Gives readers an unparalleled insight into the latest pattern recognition and signal analysis technologies, modeling, and applications
Book Synopsis Biomedical Image Analysis by : Rangaraj M. Rangayyan
Download or read book Biomedical Image Analysis written by Rangaraj M. Rangayyan and published by CRC Press. This book was released on 2004-12-30 with total page 1312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computers have become an integral part of medical imaging systems and are used for everything from data acquisition and image generation to image display and analysis. As the scope and complexity of imaging technology steadily increase, more advanced techniques are required to solve the emerging challenges. Biomedical Image Analysis demonstr
Book Synopsis Medical Image Recognition, Segmentation and Parsing by : S. Kevin Zhou
Download or read book Medical Image Recognition, Segmentation and Parsing written by S. Kevin Zhou and published by Academic Press. This book was released on 2015-12-11 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects Methods and theories for medical image recognition, segmentation and parsing of multiple objects Efficient and effective machine learning solutions based on big datasets Selected applications of medical image parsing using proven algorithms Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets Includes algorithms for recognizing and parsing of known anatomies for practical applications
Author :Thomas Martin Deserno Publisher :Springer Science & Business Media ISBN 13 :3642158161 Total Pages :617 pages Book Rating :4.6/5 (421 download)
Book Synopsis Biomedical Image Processing by : Thomas Martin Deserno
Download or read book Biomedical Image Processing written by Thomas Martin Deserno and published by Springer Science & Business Media. This book was released on 2011-03-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become an important option for health care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlighting recent advances that have been made in academics. Color figures are used extensively to illustrate the methods and help the reader to understand the complex topics.
Book Synopsis Medical Image Processing, Reconstruction and Analysis by : Jiri Jan
Download or read book Medical Image Processing, Reconstruction and Analysis written by Jiri Jan and published by CRC Press. This book was released on 2019-08-30 with total page 619 pages. Available in PDF, EPUB and Kindle. Book excerpt: Differently oriented specialists and students involved in image processing and analysis need to have a firm grasp of concepts and methods used in this now widely utilized area. This book aims at being a single-source reference providing such foundations in the form of theoretical yet clear and easy to follow explanations of underlying generic concepts. Medical Image Processing, Reconstruction and Analysis – Concepts and Methods explains the general principles and methods of image processing and analysis, focusing namely on applications used in medical imaging. The content of this book is divided into three parts: Part I – Images as Multidimensional Signals provides the introduction to basic image processing theory, explaining it for both analogue and digital image representations. Part II – Imaging Systems as Data Sources offers a non-traditional view on imaging modalities, explaining their principles influencing properties of the obtained images that are to be subsequently processed by methods described in this book. Newly, principles of novel modalities, as spectral CT, functional MRI, ultrafast planar-wave ultrasonography and optical coherence tomography are included. Part III – Image Processing and Analysis focuses on tomographic image reconstruction, image fusion and methods of image enhancement and restoration; further it explains concepts of low-level image analysis as texture analysis, image segmentation and morphological transforms. A new chapter deals with selected areas of higher-level analysis, as principal and independent component analysis and particularly the novel analytic approach based on deep learning. Briefly, also the medical image-processing environment is treated, including processes for image archiving and communication. Features Presents a theoretically exact yet understandable explanation of image processing and analysis concepts and methods Offers practical interpretations of all theoretical conclusions, as derived in the consistent explanation Provides a concise treatment of a wide variety of medical imaging modalities including novel ones, with respect to properties of provided image data
