Author: Alejandro Frangi
Publisher: Academic Press
ISBN: 0128136588
Category : Technology & Engineering
Languages : en
Pages : 700
Book Description
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. - An authoritative presentation of key concepts and methods from experts in the field - Sections clearly explaining key methodological principles within relevant medical applications - Self-contained chapters enable the text to be used on courses with differing structures - A representative selection of modern topics and techniques in medical image computing - Focus on medical image computing as an enabling technology to tackle unmet clinical needs - Presentation of traditional and machine learning approaches to medical image computing
Medical Image Analysis
Author: Alejandro Frangi
Publisher: Academic Press
ISBN: 0128136588
Category : Technology & Engineering
Languages : en
Pages : 700
Book Description
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. - An authoritative presentation of key concepts and methods from experts in the field - Sections clearly explaining key methodological principles within relevant medical applications - Self-contained chapters enable the text to be used on courses with differing structures - A representative selection of modern topics and techniques in medical image computing - Focus on medical image computing as an enabling technology to tackle unmet clinical needs - Presentation of traditional and machine learning approaches to medical image computing
Publisher: Academic Press
ISBN: 0128136588
Category : Technology & Engineering
Languages : en
Pages : 700
Book Description
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. - An authoritative presentation of key concepts and methods from experts in the field - Sections clearly explaining key methodological principles within relevant medical applications - Self-contained chapters enable the text to be used on courses with differing structures - A representative selection of modern topics and techniques in medical image computing - Focus on medical image computing as an enabling technology to tackle unmet clinical needs - Presentation of traditional and machine learning approaches to medical image computing
Topics in Medical Image Processing and Computational Vision
Author: Joao Manuel R.S. Tavares
Publisher: Springer Science & Business Media
ISBN: 9400707266
Category : Technology & Engineering
Languages : en
Pages : 312
Book Description
The sixteen chapters included in this book were written by invited experts of international recognition and address important issues in Medical Image Processing and Computational Vision, including: Object Recognition, Object Detection, Object Tracking, Pose Estimation, Facial Expression Recognition, Image Retrieval, Data Mining, Automatic Video Understanding and Management, Edges Detection, Image Segmentation, Modelling and Simulation, Medical thermography, Database Systems, Synthetic Aperture Radar and Satellite Imagery. Different applications are addressed and described throughout the book, comprising: Object Recognition and Tracking, Facial Expression Recognition, Image Database, Plant Disease Classification, Video Understanding and Management, Image Processing, Image Segmentation, Bio-structure Modelling and Simulation, Medical Imaging, Image Classification, Medical Diagnosis, Urban Areas Classification, Land Map Generation. The book brings together the current state-of-the-art in the various multi-disciplinary solutions for Medical Image Processing and Computational Vision, including research, techniques, applications and new trends contributing to the development of the related areas.
Publisher: Springer Science & Business Media
ISBN: 9400707266
Category : Technology & Engineering
Languages : en
Pages : 312
Book Description
The sixteen chapters included in this book were written by invited experts of international recognition and address important issues in Medical Image Processing and Computational Vision, including: Object Recognition, Object Detection, Object Tracking, Pose Estimation, Facial Expression Recognition, Image Retrieval, Data Mining, Automatic Video Understanding and Management, Edges Detection, Image Segmentation, Modelling and Simulation, Medical thermography, Database Systems, Synthetic Aperture Radar and Satellite Imagery. Different applications are addressed and described throughout the book, comprising: Object Recognition and Tracking, Facial Expression Recognition, Image Database, Plant Disease Classification, Video Understanding and Management, Image Processing, Image Segmentation, Bio-structure Modelling and Simulation, Medical Imaging, Image Classification, Medical Diagnosis, Urban Areas Classification, Land Map Generation. The book brings together the current state-of-the-art in the various multi-disciplinary solutions for Medical Image Processing and Computational Vision, including research, techniques, applications and new trends contributing to the development of the related areas.
Computer Vision In Medical Imaging
Author: Chi Hau Chen
Publisher: World Scientific
ISBN: 9814460958
Category : Computers
Languages : en
Pages : 410
Book Description
The major progress in computer vision allows us to make extensive use of medical imaging data to provide us better diagnosis, treatment and predication of diseases. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information from image sequence and provide 3D and 4D information that helps with better human understanding. Many powerful tools have been available through image segmentation, machine learning, pattern classification, tracking, reconstruction to bring much needed quantitative information not easily available by trained human specialists. The aim of the book is for both medical imaging professionals to acquire and interpret the data, and computer vision professionals to provide enhanced medical information by using computer vision techniques. The final objective is to benefit the patients without adding to the already high medical costs.
Publisher: World Scientific
ISBN: 9814460958
Category : Computers
Languages : en
Pages : 410
Book Description
The major progress in computer vision allows us to make extensive use of medical imaging data to provide us better diagnosis, treatment and predication of diseases. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information from image sequence and provide 3D and 4D information that helps with better human understanding. Many powerful tools have been available through image segmentation, machine learning, pattern classification, tracking, reconstruction to bring much needed quantitative information not easily available by trained human specialists. The aim of the book is for both medical imaging professionals to acquire and interpret the data, and computer vision professionals to provide enhanced medical information by using computer vision techniques. The final objective is to benefit the patients without adding to the already high medical costs.
Emerging Topics in Computer Vision and Its Applications
Author: C. H. Chen
Publisher: World Scientific
ISBN: 9814343005
Category : Computers
Languages : en
Pages : 508
Book Description
This book gives a comprehensive overview of the most advanced theories, methodologies and applications in computer vision. Particularly, it gives an extensive coverage of 3D and robotic vision problems. Example chapters featured are Fourier methods for 3D surface modeling and analysis, use of constraints for calibration-free 3D Euclidean reconstruction, novel photogeometric methods for capturing static and dynamic objects, performance evaluation of robot localization methods in outdoor terrains, integrating 3D vision with force/tactile sensors, tracking via in-floor sensing, self-calibration of camera networks, etc. Some unique applications of computer vision in marine fishery, biomedical issues, driver assistance, are also highlighted.
Publisher: World Scientific
ISBN: 9814343005
Category : Computers
Languages : en
Pages : 508
Book Description
This book gives a comprehensive overview of the most advanced theories, methodologies and applications in computer vision. Particularly, it gives an extensive coverage of 3D and robotic vision problems. Example chapters featured are Fourier methods for 3D surface modeling and analysis, use of constraints for calibration-free 3D Euclidean reconstruction, novel photogeometric methods for capturing static and dynamic objects, performance evaluation of robot localization methods in outdoor terrains, integrating 3D vision with force/tactile sensors, tracking via in-floor sensing, self-calibration of camera networks, etc. Some unique applications of computer vision in marine fishery, biomedical issues, driver assistance, are also highlighted.
Guide to Medical Image Analysis
Author: Klaus D. Toennies
Publisher: Springer Science & Business Media
ISBN: 144712751X
Category : Computers
Languages : en
Pages : 477
Book Description
This book presents a comprehensive overview of medical image analysis. Practical in approach, the text is uniquely structured by potential applications. Features: presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques, reconstruction techniques and image artefacts; discusses the archival and transfer of images, including the HL7 and DICOM standards; presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing; examines various feature detection and segmentation techniques, together with methods for computing a registration or normalisation transformation; explores object detection, as well as classification based on segment attributes such as shape and appearance; reviews the validation of an analysis method; includes appendices on Markov random field optimization, variational calculus and principal component analysis.
Publisher: Springer Science & Business Media
ISBN: 144712751X
Category : Computers
Languages : en
Pages : 477
Book Description
This book presents a comprehensive overview of medical image analysis. Practical in approach, the text is uniquely structured by potential applications. Features: presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques, reconstruction techniques and image artefacts; discusses the archival and transfer of images, including the HL7 and DICOM standards; presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing; examines various feature detection and segmentation techniques, together with methods for computing a registration or normalisation transformation; explores object detection, as well as classification based on segment attributes such as shape and appearance; reviews the validation of an analysis method; includes appendices on Markov random field optimization, variational calculus and principal component analysis.
Research Developments in Computer Vision and Image Processing
Author: Rajeev Srivastava
Publisher:
ISBN: 9781466645585
Category : Computer vision
Languages : en
Pages : 0
Book Description
"This book brings together various research methodologies and trends in emerging areas of application of computer vision and image processing for those interested in the research developments of this rapidly growing field"--
Publisher:
ISBN: 9781466645585
Category : Computer vision
Languages : en
Pages : 0
Book Description
"This book brings together various research methodologies and trends in emerging areas of application of computer vision and image processing for those interested in the research developments of this rapidly growing field"--
Deep Learning in Medical Image Analysis
Author: Gobert Lee
Publisher: Springer Nature
ISBN: 3030331288
Category : Medical
Languages : en
Pages : 184
Book Description
This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.
Publisher: Springer Nature
ISBN: 3030331288
Category : Medical
Languages : en
Pages : 184
Book Description
This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.
Decision Forests for Computer Vision and Medical Image Analysis
Author: Antonio Criminisi
Publisher: Springer Science & Business Media
ISBN: 1447149297
Category : Computers
Languages : en
Pages : 367
Book Description
This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.
Publisher: Springer Science & Business Media
ISBN: 1447149297
Category : Computers
Languages : en
Pages : 367
Book Description
This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.
Introduction to Medical Image Analysis
Author: Rasmus R. Paulsen
Publisher: Springer Nature
ISBN: 303039364X
Category : Computers
Languages : en
Pages : 185
Book Description
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.
Publisher: Springer Nature
ISBN: 303039364X
Category : Computers
Languages : en
Pages : 185
Book Description
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.
Advanced Machine Vision Paradigms for Medical Image Analysis
Author: Tapan K. Gandhi
Publisher: Academic Press
ISBN: 0128192968
Category : Computers
Languages : en
Pages : 310
Book Description
Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. - Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence - Highlights the advancement of conventional approaches in the field of medical image processing - Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis
Publisher: Academic Press
ISBN: 0128192968
Category : Computers
Languages : en
Pages : 310
Book Description
Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. - Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence - Highlights the advancement of conventional approaches in the field of medical image processing - Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis