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Level Set And Pde Based Reconstruction Methods In Imaging
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Book Synopsis Level Set and PDE Based Reconstruction Methods in Imaging by : Martin Burger
Download or read book Level Set and PDE Based Reconstruction Methods in Imaging written by Martin Burger and published by Springer. This book was released on 2013-10-17 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes readers on a tour through modern methods in image analysis and reconstruction based on level set and PDE techniques, the major focus being on morphological and geometric structures in images. The aspects covered include edge-sharpening image reconstruction and denoising, segmentation and shape analysis in images, and image matching. For each, the lecture notes provide insights into the basic analysis of modern variational and PDE-based techniques, as well as computational aspects and applications.
Book Synopsis Splitting Methods in Communication, Imaging, Science, and Engineering by : Roland Glowinski
Download or read book Splitting Methods in Communication, Imaging, Science, and Engineering written by Roland Glowinski and published by Springer. This book was released on 2017-01-05 with total page 820 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about computational methods based on operator splitting. It consists of twenty-three chapters written by recognized splitting method contributors and practitioners, and covers a vast spectrum of topics and application areas, including computational mechanics, computational physics, image processing, wireless communication, nonlinear optics, and finance. Therefore, the book presents very versatile aspects of splitting methods and their applications, motivating the cross-fertilization of ideas.
Book Synopsis Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging by : Ke Chen
Download or read book Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging written by Ke Chen and published by Springer Nature. This book was released on 2023-02-24 with total page 1981 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook gathers together the state of the art on mathematical models and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision. Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.
Book Synopsis Level Set Method in Medical Imaging Segmentation by : Ayman El-Baz
Download or read book Level Set Method in Medical Imaging Segmentation written by Ayman El-Baz and published by CRC Press. This book was released on 2019-06-26 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Level set methods are numerical techniques which offer remarkably powerful tools for understanding, analyzing, and computing interface motion in a host of settings. When used for medical imaging analysis and segmentation, the function assigns a label to each pixel or voxel and optimality is defined based on desired imaging properties. This often includes a detection step to extract specific objects via segmentation. This allows for the segmentation and analysis problem to be formulated and solved in a principled way based on well-established mathematical theories. Level set method is a great tool for modeling time varying medical images and enhancement of numerical computations.
Book Synopsis Geometric Level Set Methods in Imaging, Vision, and Graphics by : Stanley Osher
Download or read book Geometric Level Set Methods in Imaging, Vision, and Graphics written by Stanley Osher and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is, for the first time, a book that clearly explains and applies new level set methods to problems and applications in computer vision, graphics, and imaging. It is an essential compilation of survey chapters from the leading researchers in the field. The applications of the methods are emphasized.
Book Synopsis Diagnostic and Therapeutic Nuclear Medicine for Neuroendocrine Tumors by : Karel Pacak
Download or read book Diagnostic and Therapeutic Nuclear Medicine for Neuroendocrine Tumors written by Karel Pacak and published by Humana Press. This book was released on 2016-12-26 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the most novel approaches and cutting-edge clinical and scientific information regarding radionuclide imaging and therapies for neuroendocrine tumors, this clinical guidebook represents a unique collaborative effort between endocrinologists, nuclear physicians, oncologists, surgeons, physicists, radio-pharmacists and geneticists. It begins with the embryology, classification and molecular genetics of gastroenteropancreatic neuroendocrine tumors and carcinoids, chromaffin cell tumors, and MEN1- and MEN2-related tumors. Following a chapter on radiopharmaceuticals in neuroendocrine imaging, it turns to the physics and technology of current and cutting-edge radiology, including SPECT/CT and PET/CT and PET/MR. Discussing of radionuclide imaging covers the tumors mentioned above, as well as pulmonary and thymic neuroendocrine tumors and medullary thyroid carcinoma. A presentation of radionuclide therapies follows, including 131I-MIBG therapy, somatostatin receptor-based therapy, and alpha radionuclide therapy, as well as the role of nanoparticles. Comprehensive and up-to-date, Diagnostic and Therapeutic Nuclear Medicine for Neuroendocrine Tumors will assist and guide physicians who encounter patients with these conditions, either from a diagnostic or therapeutic standpoint, and particularly emphasizes the current and emerging medical devices and imaging and therapeutic options.
Book Synopsis Regularized Image Reconstruction in Parallel MRI with MATLAB by : Joseph Suresh Paul
Download or read book Regularized Image Reconstruction in Parallel MRI with MATLAB written by Joseph Suresh Paul and published by CRC Press. This book was released on 2019-11-05 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regularization becomes an integral part of the reconstruction process in accelerated parallel magnetic resonance imaging (pMRI) due to the need for utilizing the most discriminative information in the form of parsimonious models to generate high quality images with reduced noise and artifacts. Apart from providing a detailed overview and implementation details of various pMRI reconstruction methods, Regularized image reconstruction in parallel MRI with MATLAB examples interprets regularized image reconstruction in pMRI as a means to effectively control the balance between two specific types of error signals to either improve the accuracy in estimation of missing samples, or speed up the estimation process. The first type corresponds to the modeling error between acquired and their estimated values. The second type arises due to the perturbation of k-space values in autocalibration methods or sparse approximation in the compressed sensing based reconstruction model. Features: Provides details for optimizing regularization parameters in each type of reconstruction. Presents comparison of regularization approaches for each type of pMRI reconstruction. Includes discussion of case studies using clinically acquired data. MATLAB codes are provided for each reconstruction type. Contains method-wise description of adapting regularization to optimize speed and accuracy. This book serves as a reference material for researchers and students involved in development of pMRI reconstruction methods. Industry practitioners concerned with how to apply regularization in pMRI reconstruction will find this book most useful.
Book Synopsis Modeling, Simulation and Optimization of Fluid Dynamic Applications by : Armin Iske
Download or read book Modeling, Simulation and Optimization of Fluid Dynamic Applications written by Armin Iske and published by Springer Nature. This book was released on 2023-12-13 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes recent collaborations combining the expertise of applied mathematicians, engineers and geophysicists within a research training group (RTG) on "Modeling, Simulation and Optimization of Fluid Dynamic Applications”, funded by the Deutsche Forschungsgemeinschaft (DFG). The focus is on mathematical modeling, adaptive discretization, approximation strategies and shape optimization with PDEs. The balanced research program is based on the guiding principle that mathematics drives applications and is inspired by applications. With this leitmotif the RTG advances research in Modeling, Simulation and Optimization by an interdisciplinary approach, i.e., to stimulate fundamental education and research by highly complex applications and at the simultaneously transfer tailored mathematical methods to applied sciences. The reported research involves nine projects and addresses challenging fluid dynamic problems inspired by applied sciences, such as climate research & meteorology, energy, aerospace & marine engineering, or medicine. More fundamental research concerning analysis, approximation and numerics is also covered. The material represents a successful attempt to exchange research paradigms between different disciplines and thus displays a modern approach to basic research into scientifically and societally relevant contemporary problems.
Book Synopsis Introduction to Inverse Problems in Imaging by : M. Bertero
Download or read book Introduction to Inverse Problems in Imaging written by M. Bertero and published by CRC Press. This book was released on 2021-12-20 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully updated throughout and with several new chapters, this second edition of Introduction to Inverse Problems in Imaging guides advanced undergraduate and graduate students in physics, computer science, mathematics and engineering through the principles of linear inverse problems, in addition to methods of their approximate solution and their practical applications in imaging. This second edition contains new chapters on edge-preserving and sparsity-enforcing regularization in addition to maximum likelihood methods and Bayesian regularization for Poisson data. The level of mathematical treatment is kept as low as possible to make the book suitable for a wide range of students from different backgrounds, with readers needing just a rudimentary understanding of analysis, geometry, linear algebra, probability theory, and Fourier analysis. The authors concentrate on presenting easily implementable and fast solution algorithms, and this second edition is accompanied by numerical examples throughout. It will provide readers with the appropriate background needed for a clear understanding of the essence of inverse problems (ill-posedness and its cure) and, consequently, for an intelligent assessment of the rapidly growing literature on these problems. Key features: Provides an accessible introduction to the topic while keeping mathematics to a minimum Interdisciplinary topic with growing relevance and wide-ranging applications Accompanied by numerical examples throughout
Book Synopsis Processing, Analyzing and Learning of Images, Shapes, and Forms: by : Xue-Cheng Tai
Download or read book Processing, Analyzing and Learning of Images, Shapes, and Forms: written by Xue-Cheng Tai and published by North Holland. This book was released on 2019-10 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Covers contemporary developments relating to the analysis and learning of images, shapes and forms Presents mathematical models and quick computational techniques relating to the topic Provides broad coverage, with sample chapters presenting content on Alternating Diffusion and Generating Structured TV-based Priors and Associated Primal-dual Methods
Book Synopsis Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2 by :
Download or read book Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2 written by and published by Elsevier. This book was released on 2019-10-16 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Covers contemporary developments relating to the analysis and learning of images, shapes and forms Presents mathematical models and quick computational techniques relating to the topic Provides broad coverage, with sample chapters presenting content on Alternating Diffusion and Generating Structured TV-based Priors and Associated Primal-dual Methods
Book Synopsis Scale Space and Variational Methods in Computer Vision by : Abderrahim Elmoataz
Download or read book Scale Space and Variational Methods in Computer Vision written by Abderrahim Elmoataz and published by Springer Nature. This book was released on 2021-04-29 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 8th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2021, which took place during May 16-20, 2021. The conference was planned to take place in Cabourg, France, but changed to an online format due to the COVID-19 pandemic. The 45 papers included in this volume were carefully reviewed and selected from a total of 64 submissions. They were organized in topical sections named as follows: scale space and partial differential equations methods; flow, motion and registration; optimization theory and methods in imaging; machine learning in imaging; segmentation and labelling; restoration, reconstruction and interpolation; and inverse problems in imaging.
Book Synopsis Inverse Problems and Imaging by : Luis L. Bonilla
Download or read book Inverse Problems and Imaging written by Luis L. Bonilla and published by Springer. This book was released on 2009-06-19 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays we are facing numerous and important imaging problems: nondestructive testing of materials, monitoring of industrial processes, enhancement of oil production by efficient reservoir characterization, emerging developments in noninvasive imaging techniques for medical purposes - computerized tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), X-ray and ultrasound tomography, etc. In the CIME Summer School on Imaging (Martina Franca, Italy 2002), leading experts in mathematical techniques and applications presented broad and useful introductions for non-experts and practitioners alike to many aspects of this exciting field. The volume contains part of the above lectures completed and updated by additional contributions on other related topics.
Book Synopsis Level Set Method in Medical Imaging Segmentation by : Ayman El-Baz
Download or read book Level Set Method in Medical Imaging Segmentation written by Ayman El-Baz and published by CRC Press. This book was released on 2019-06-26 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Level set methods are numerical techniques which offer remarkably powerful tools for understanding, analyzing, and computing interface motion in a host of settings. When used for medical imaging analysis and segmentation, the function assigns a label to each pixel or voxel and optimality is defined based on desired imaging properties. This often includes a detection step to extract specific objects via segmentation. This allows for the segmentation and analysis problem to be formulated and solved in a principled way based on well-established mathematical theories. Level set method is a great tool for modeling time varying medical images and enhancement of numerical computations.
Book Synopsis Scale Space and Variational Methods in Computer Vision by : Luca Calatroni
Download or read book Scale Space and Variational Methods in Computer Vision written by Luca Calatroni and published by Springer Nature. This book was released on 2023-05-09 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, which took place in Santa Margherita di Pula, Italy, in May 2023. The 57 papers presented in this volume were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Inverse Problems in Imaging; Machine and Deep Learning in Imaging; Optimization for Imaging: Theory and Methods; Scale Space, PDEs, Flow, Motion and Registration.
Book Synopsis Geometric Analysis and PDEs by : Matthew J. Gursky
Download or read book Geometric Analysis and PDEs written by Matthew J. Gursky and published by Springer. This book was released on 2009-07-31 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains lecture notes on key topics in geometric analysis, a growing mathematical subject which uses analytical techniques, mostly of partial differential equations, to treat problems in differential geometry and mathematical physics.
Book Synopsis Image Processing Based on Partial Differential Equations by : Xue-Cheng Tai
Download or read book Image Processing Based on Partial Differential Equations written by Xue-Cheng Tai and published by Springer Science & Business Media. This book was released on 2006-11-22 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book publishes a collection of original scientific research articles that address the state-of-art in using partial differential equations for image and signal processing. Coverage includes: level set methods for image segmentation and construction, denoising techniques, digital image inpainting, image dejittering, image registration, and fast numerical algorithms for solving these problems.
