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| Author | : Bart M. Haar Romeny |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 470 |
| Release | : 2008-10-24 |
| Genre | : Computers |
| ISBN | : 140208840X |
Download Front-End Vision and Multi-Scale Image Analysis Book in PDF, ePub and Kindle
Many approaches have been proposed to solve the problem of finding the optic flow field of an image sequence. Three major classes of optic flow computation techniques can discriminated (see for a good overview Beauchemin and Barron IBeauchemin19951): gradient based (or differential) methods; phase based (or frequency domain) methods; correlation based (or area) methods; feature point (or sparse data) tracking methods; In this chapter we compute the optic flow as a dense optic flow field with a multi scale differential method. The method, originally proposed by Florack and Nielsen [Florack1998a] is known as the Multiscale Optic Flow Constrain Equation (MOFCE). This is a scale space version of the well known computer vision implementation of the optic flow constraint equation, as originally proposed by Horn and Schunck [Horn1981]. This scale space variation, as usual, consists of the introduction of the aperture of the observation in the process. The application to stereo has been described by Maas et al. [Maas 1995a, Maas 1996a]. Of course, difficulties arise when structure emerges or disappears, such as with occlusion, cloud formation etc. Then knowledge is needed about the processes and objects involved. In this chapter we focus on the scale space approach to the local measurement of optic flow, as we may expect the visual front end to do. 17. 2 Motion detection with pairs of receptive fields As a biologically motivated start, we begin with discussing some neurophysiological findings in the visual system with respect to motion detection.
| Author | : Reinhard Klette |
| Publisher | : Springer |
| Total Pages | : 296 |
| Release | : 2003-06-29 |
| Genre | : Computers |
| ISBN | : 354045134X |
Download Multi-Image Analysis Book in PDF, ePub and Kindle
This book constitutes the thoroughly refereed post-proceedings of the 10th International Workshop on Theoretical Foundations of Computer Vision, held at Dagstuhl Castle, Germany, in March 2000. The 20 revised full papers presented have been through two rounds of reviewing, selection, and revision and give a representative assessment of the foundational issues in multiple-image processing. The papers are organized in topical sections on 3D data acquisition and sensor design, multi-image analysis, data fusion in 3D scene description, and applied 3D vision and virtual reality.
| Author | : Gobert Lee |
| Publisher | : Springer Nature |
| Total Pages | : 184 |
| Release | : 2020-02-06 |
| Genre | : Medical |
| ISBN | : 3030331288 |
Download Deep Learning in Medical Image Analysis Book in PDF, ePub and Kindle
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.
| Author | : Scott Thomas Acton |
| Publisher | : Morgan & Claypool Publishers |
| Total Pages | : 153 |
| Release | : 2006 |
| Genre | : Computers |
| ISBN | : 1598290185 |
Download Biomedical Image Analysis Book in PDF, ePub and Kindle
Annotation Biomedical Image Analysis: Tracking addresses methods for extracting image information from biological/medical images for use in tracking biological targets. Here, and in the forthcoming companion Biomedical Image Analysis: Segmentation (Morgan & Claypool, ISBN: 1598290207), the authors concentrate on aspects of image analysis rather than the modalities or the imaging process itself. This lecture will be a valuable resource for graduate students, faculty, and industrial/governmental researchers interested in applications of imaging, or more specifically, biomedical imaging. It is written from first principles and will be accessible to a broad readership. Key Features:?Methods for tracking using active contours, together with a discussion of selection of parameters and weights?Methods for implementing snakes by way of dynamic programming?Probabilistic methods for tracking, with a description of the Kalman filter?Coverage of factored sampling and Monte Carlo methods, including the newly emerging particle filter?A summary of important new advances in target tracking, including multi-target tracking techniquesDescription of shape-based methods for biomedical image analysis.
| Author | : Gonzalez, Fabio A. |
| Publisher | : IGI Global |
| Total Pages | : 390 |
| Release | : 2009-12-31 |
| Genre | : Computers |
| ISBN | : 1605669571 |
Download Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques Book in PDF, ePub and Kindle
Medical images are at the base of many routine clinical decisions and their influence continues to increase in many fields of medicine. Since the last decade, computers have become an invaluable tool for supporting medical image acquisition, processing, organization and analysis. Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques provides a panorama of the current boundary between biomedical complexity coming from the medical image context and the multiple techniques which have been used for solving many of these problems. This innovative publication serves as a leading industry reference as well as a source of creative ideas for applications of medical issues.
| Author | : Atam P. Dhawan |
| Publisher | : John Wiley & Sons |
| Total Pages | : 396 |
| Release | : 2011-03-29 |
| Genre | : Technology & Engineering |
| ISBN | : 0470922893 |
Download Medical Image Analysis Book in PDF, ePub and Kindle
The expanded and revised edition will split Chapter 4 to include more details and examples in FMRI, DTI, and DWI for MR image modalities. The book will also expand ultrasound imaging to 3-D dynamic contrast ultrasound imaging in a separate chapter. A new chapter on Optical Imaging Modalities elaborating microscopy, confocal microscopy, endoscopy, optical coherent tomography, fluorescence and molecular imaging will be added. Another new chapter on Simultaneous Multi-Modality Medical Imaging including CT-SPECT and CT-PET will also be added. In the image analysis part, chapters on image reconstructions and visualizations will be significantly enhanced to include, respectively, 3-D fast statistical estimation based reconstruction methods, and 3-D image fusion and visualization overlaying multi-modality imaging and information. A new chapter on Computer-Aided Diagnosis and image guided surgery, and surgical and therapeutic intervention will also be added. A companion site containing power point slides, author biography, corrections to the first edition and images from the text can be found here: ftp://ftp.wiley.com/public/sci_tech_med/medical_image/ Send an email to: [email protected] to obtain a solutions manual. Please include your affiliation in your email.
| Author | : Emanuele Trucco |
| Publisher | : Academic Press |
| Total Pages | : 506 |
| Release | : 2019-11-19 |
| Genre | : Computers |
| ISBN | : 0081028172 |
Download Computational Retinal Image Analysis Book in PDF, ePub and Kindle
Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. Provides a unique, well-structured and integrated overview of retinal image analysis Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care Includes plans and aspirations of companies and professional bodies
| Author | : S. Kevin Zhou |
| Publisher | : Academic Press |
| Total Pages | : 544 |
| Release | : 2023-12-01 |
| Genre | : Computers |
| ISBN | : 0323858880 |
Download Deep Learning for Medical Image Analysis Book in PDF, ePub and Kindle
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
| Author | : A. Rosenfeld |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 392 |
| Release | : 2013-03-09 |
| Genre | : Computers |
| ISBN | : 3642515908 |
Download Multiresolution Image Processing and Analysis Book in PDF, ePub and Kindle
This book results from a Workshop on Multiresolution Image Processing and Analysis, held in Leesburg, VA on July 19-21, 1982. It contains updated ver sions of most of the papers that were presented at the Workshop, as well as new material added by the authors. Four of the presented papers were not available for inclusion in the book: D. Sabbah, A computing with connections approach to visual recognition; R. M. Haralick, Fitting the gray tone intensity surface as a function of neighborhood size; E. M. Riseman, Hierarchical boundary formation; and W. L. Mahaffey, L. S. Davis, and J. K. Aggarwal, Region correspondence in multi-resolution images taken from dynamic scenes. The number and variety of papers indicates the timeliness of the H0rkshop. Multiresolution methods are rapidly gaining recognition as an important theme in image processing and analysis. I would like to express my thanks to the National Science Foundation for their support of the Workshop under Grant MCS-82-05942; to Barbara Hope for organizing and administering the Workshop; to Janet Salzman and Fran Cohen, for retyping the papers; and above all, to the speakers and other partici pants, for making the Workshop possible.
| Author | : Paul L. Rosin |
| Publisher | : Springer Nature |
| Total Pages | : 524 |
| Release | : 2019-10-26 |
| Genre | : Computers |
| ISBN | : 3030286037 |
Download RGB-D Image Analysis and Processing Book in PDF, ePub and Kindle
This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.
