Processing Analyzing And Learning Of Images Shapes And Forms Part 1
Download Processing Analyzing And Learning Of Images Shapes And Forms Part 1 PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Processing Analyzing And Learning Of Images Shapes And Forms Part 1 book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2
Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2, Volume 20, surveys the contemporary developments relating to the analysis and learning of images, shapes and forms, covering mathematical models and quick computational techniques. Chapter cover Alternating Diffusion: A Geometric Approach for Sensor Fusion, Generating Structured TV-based Priors and Associated Primal-dual Methods, Graph-based Optimization Approaches for Machine Learning, Uncertainty Quantification and Networks, Extrinsic Shape Analysis from Boundary Representations, Efficient Numerical Methods for Gradient Flows and Phase-field Models, Recent Advances in Denoising of Manifold-Valued Images, Optimal Registration of Images, Surfaces and Shapes, and much more.
Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 1
Processing, Analyzing and Learning of Images, Shapes, and Forms: Volume 19, Part One provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms. It covers mathematical models as well as fast computational techniques, and includes new chapters on Alternating diffusion: a geometric approach for sensor fusion, Shape Correspondence and Functional Maps, Geometric models for perception-based image processing, Decomposition schemes for nonconvex composite minimization: theory and applications, Low rank matrix recovery: algorithms and theory, Geometry and learning for deformation shape correspondence, and Factoring scene layout from monocular images in presence of occlusion. - Presents a contemporary view on the topic, comprehensively covering the newest developments and content - Provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms
Quantification of Biophysical Parameters in Medical Imaging
The second edition of this book offers six new chapters covering the latest developments in quantitative medical imaging, including artificial intelligence, MRI mapping, sonography, elastography and cardiac CT. All the other existing chapters have been updated and expanded, many with new text and figures, to reflect the rapid translation and advancement of technology in this exciting area of biomedical research. This updated edition presents fundamental knowledge on the imaging quantification of biophysical parameters for clinical diagnostic purposes. Clinical imaging scanners are considered by the authors as physical measurement systems capable of quantifying intrinsic parameters for the representation of the constitution and biophysical properties of tissues in vivo. In one respect, this approach fosters the development of new imaging methods for highly reproducible, system-independent, and quantitative biomarkers. These methods are greatly detailed in the book. Alternatively, this new edition equips the reader with a better understanding of how the physical properties of tissues interact with signal generation in medical imaging, opening up new insights into the complex and fascinating relationship between structure and function in living tissues. This updated edition is of interest to all those who recognize the limitations of clinical diagnosis based primarily on visual inspection of images, and who wish to learn more about the diagnostic potential of quantitative, biophysically-based medical imaging markers, as well as the challenges posed by the scarcity of such markers for next-generation imaging technologies.