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A Study Of Modified Fisher Scoring Algorithms For Statistical Image Reconstruction In Emission Tomography
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Book Synopsis A Study of Modified Fisher Scoring Algorithms for Statistical Image Reconstruction in Emission Tomography by : Khairil Anwar Notodiputro
Download or read book A Study of Modified Fisher Scoring Algorithms for Statistical Image Reconstruction in Emission Tomography written by Khairil Anwar Notodiputro and published by . This book was released on 1991 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Convergent Algorithms for Statistical Image Reconstruction in Emission Tomography by : Sangtae Ahn
Download or read book Convergent Algorithms for Statistical Image Reconstruction in Emission Tomography written by Sangtae Ahn and published by . This book was released on 2004 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modified Fisher Scoring Algorithms Using Jacobi Or Gauss-Seidel Subiterations by : Jun Ma
Download or read book Modified Fisher Scoring Algorithms Using Jacobi Or Gauss-Seidel Subiterations written by Jun Ma and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a parameter estimation problem with large numbers of unknown parameters, traditional algorithms such as fisher scoring and Newton-Raphson become impractical. A typical case is solution by discretization of linear inverse problems; an example is medical image reconstruction from projections. This article introduces a modification to the Fisher scoring method. Instead of solving the linear system of equations of each Fisher scoring iteration exactly, the solution of these equations is approximated by using the Jacobi or Gauss-Seidel scheme. Simulation studies show that these modified algorithms, especially the one with Gauss-Seidel scheme, exhibit much faster convergence than competitors such as the EM algorithm.
Book Synopsis Bulletin - Institute of Mathematical Statistics by : Institute of Mathematical Statistics
Download or read book Bulletin - Institute of Mathematical Statistics written by Institute of Mathematical Statistics and published by . This book was released on 1994 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modified Fisher Scoring for Maximum Likelihood Image Reconstruction by : Khairil Anwar Notodiputro
Download or read book Modified Fisher Scoring for Maximum Likelihood Image Reconstruction written by Khairil Anwar Notodiputro and published by . This book was released on 1989 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Residual Correction Algorithms for Statistical Image Reconstruction in Positron Emission Tomography by : Lin Fu
Download or read book Residual Correction Algorithms for Statistical Image Reconstruction in Positron Emission Tomography written by Lin Fu and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Positron emission tomography (PET) is a radionuclide imaging modality that plays important roles in visualizing, targeting, and quantifying functional processes in vivo. High-resolution and quantitative PET images are reconstructed by solving large-scale inverse problems with iterative methods that incorporate accurate physics and noise modeling of the imaging process. The computation demands of PET image reconstruction are rapidly increasing as higher-resolution detectors, larger imaging field-of-view, and dynamic or adaptive data acquisition modes are being adopted by modern PET scanners. The trend of the increase in the computation demands is even faster than Moore's law that describes the exponential growth in the number of transistors placed on an integrated circuit. In this project a residual correction mechanism is introduced to PET image reconstruction to create computationally efficient yet accurate tomographic reconstruction algorithms. By using residual correction, reconstruction methods are able to adopt a more simplified physical model for fast computation while retaining the accuracy of the final solution. Residual correction can accelerate existing image reconstruction packages. It allows iterative reconstruction with more accurate physical models which are currently impractical due to the high computation cost. Two illustrative applications of the residual correction approach are provided. One is image reconstruction with an object-dependent Monte Carlo based physics model. The other is image reconstruction using an ultra fast GPU-accelerated simplified geometric model.
Book Synopsis Journal of the American Statistical Association by :
Download or read book Journal of the American Statistical Association written by and published by . This book was released on 1996 with total page 1884 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Image Reconstruction for Quantitative Computed Tomography by : Joshua D. Evans
Download or read book Statistical Image Reconstruction for Quantitative Computed Tomography written by Joshua D. Evans and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical iterative reconstruction (SIR) algorithms for x-ray computed tomography (CT) have the potential to reconstruct images with less noise and systematic error than the conventional filtered backprojection (FBP) algorithm. More accurate reconstruction algorithms are important for reducing imaging dose and for a wide range of quantitative CT applications. The work presented herein investigates some potential advantages of one such statistically motivated algorithm called Alternating Minimization (AM). A simulation study is used to compare the tradeoff between noise and resolution in images reconstructed with the AM and FBP algorithms. The AM algorithm is employed with an edge-preserving penalty function, which is shown to result in images with contrast-dependent resolution. The AM algorithm always reconstructed images with less image noise than the FBP algorithm. Compared to previous studies in the literature, this is the first work to clearly illustrate that the reported noise advantage when using edge-preserving penalty functions can be highly dependent on the contrast of the object used for quantifying resolution. A polyenergetic version of the AM algorithm, which incorporates knowledge of the scanner's x-ray spectrum, is then commissioned from data acquired on a commercially available CT scanner. Homogeneous cylinders are used to assess the absolute accuracy of the polyenergetic AM algorithm and to compare systematic errors to conventional FBP reconstruction. Methods to estimate the x-ray spectrum, model the bowtie filter and measure scattered radiation are outlined which support AM reconstruction to within 0.5% of the expected ground truth. The polyenergetic AM algorithm reconstructs the cylinders with less systematic error than FBP, in terms of better image uniformity and less object-size dependence. Finally, the accuracy of a post-processing dual-energy CT (pDECT) method to non-invasively measure a material's photon cross-section information is investigated. Data is acquired on a commercial scanner for materials of known composition. Since the pDECT method has been shown to be highly sensitive to reconstructed image errors, both FBP and polyenergetic AM reconstruction are employed. Linear attenuation coefficients are estimated with residual errors of around 1% for energies of 30 keV to 1 MeV with errors rising to 3%-6% at lower energies down to 10 keV. In the ideal phantom geometry used here, the main advantage of AM reconstruction is less random cross-section uncertainty due to the improved noise performance.
Book Synopsis Penalised Image Reconstruction Algorithms for Efficient and Consistent Quantification in Emission Tomography by : Yu-Jung Tsai
Download or read book Penalised Image Reconstruction Algorithms for Efficient and Consistent Quantification in Emission Tomography written by Yu-Jung Tsai and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Image Reconstruction with Anatomical Priors in Positron Emission Tomography by : Chung Chan
Download or read book Statistical Image Reconstruction with Anatomical Priors in Positron Emission Tomography written by Chung Chan and published by . This book was released on 2008 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Speed of Estimation in Positron Emission Tomography by : Stanford University. Department of Statistics
Download or read book Speed of Estimation in Positron Emission Tomography written by Stanford University. Department of Statistics and published by . This book was released on 1988 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several algorithms for image reconstruction in positron emission tomography (PET) have been described in the medical and statistical literature. A continuous idealisation of the PET reconstruction problem is studied, considered as an example of bivariate density estimation based on indirect observations. Given a large sample of indirect observations, the size is considered of the equivalent sample of observations, whose original exact positions would allow equally accurate estimation of the image of interest. Both for indirect and for direct observations, the exact minimax rates are established for convergence of estimation, for all possible estimators, over suitable smoothness classes of functions. For indirect data and (in practice unobservable) direct data, these rates are n exp( -p/(p+2)) and (n/log n) exp( -p/(p+1)) respectively, for densities in a class corresponding to bounded square-integrable pth derivatives. Numerical values are obtained for equivalent sample sizes for a particular class of orthogonal series estimators, based on the eigenfunctions of the Radon transform. Keywords: Density estimation; Fano's lemma; Image analysis; Information theory; Inverse problems; Minimax; Orthogonal series; Radon transform; Singular value decomposition; Tomography. (JHD).
Book Synopsis Statistical Parametric Mapping: The Analysis of Functional Brain Images by : William D. Penny
Download or read book Statistical Parametric Mapping: The Analysis of Functional Brain Images written by William D. Penny and published by Elsevier. This book was released on 2011-04-28 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible
Download or read book Mixed Models written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2013-08-05 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one’s personal library.” —Journal of the American Statistical Association Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R. The new edition provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as nontraditional applications, such as regrowth curves, shapes, and images. The book features the latest topics in statistics including modeling of complex clustered or longitudinal data, modeling data with multiple sources of variation, modeling biological variety and heterogeneity, Healthy Akaike Information Criterion (HAIC), parameter multidimensionality, and statistics of image processing. Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as: Comprehensive theoretical discussions illustrated by examples and figures Over 300 exercises, end-of-section problems, updated data sets, and R subroutines Problems and extended projects requiring simulations in R intended to reinforce material Summaries of major results and general points of discussion at the end of each chapter Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.
Book Synopsis Advanced PET, SPECT, MR and Optical Imaging in Clinical and Pre-Clinical Research of Neuropsychiatric Disorders by : Boldizsar Czeh
Download or read book Advanced PET, SPECT, MR and Optical Imaging in Clinical and Pre-Clinical Research of Neuropsychiatric Disorders written by Boldizsar Czeh and published by Frontiers Media SA. This book was released on 2022-02-04 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Algorithms from THE BOOK by : Kenneth Lange
Download or read book Algorithms from THE BOOK written by Kenneth Lange and published by SIAM. This book was released on 2020-05-04 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithms are a dominant force in modern culture, and every indication is that they will become more pervasive, not less. The best algorithms are undergirded by beautiful mathematics. This text cuts across discipline boundaries to highlight some of the most famous and successful algorithms. Readers are exposed to the principles behind these examples and guided in assembling complex algorithms from simpler building blocks. Written in clear, instructive language within the constraints of mathematical rigor, Algorithms from THE BOOK includes a large number of classroom-tested exercises at the end of each chapter. The appendices cover background material often omitted from undergraduate courses. Most of the algorithm descriptions are accompanied by Julia code, an ideal language for scientific computing. This code is immediately available for experimentation. Algorithms from THE BOOK is aimed at first-year graduate and advanced undergraduate students. It will also serve as a convenient reference for professionals throughout the mathematical sciences, physical sciences, engineering, and the quantitative sectors of the biological and social sciences.
Book Synopsis Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards by :
Download or read book Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards written by and published by . This book was released on 1994 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theses on any subject submitted by the academic libraries in the UK and Ireland.
Book Synopsis Emission Tomography by : Miles N. Wernick
Download or read book Emission Tomography written by Miles N. Wernick and published by Elsevier. This book was released on 2004-12-07 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: PET and SPECT are two of today's most important medical-imaging methods, providing images that reveal subtle information about physiological processes in humans and animals. Emission Tomography: The Fundamentals of PET and SPECT explains the physics and engineering principles of these important functional-imaging methods. The technology of emission tomography is covered in detail, including historical origins, scientific and mathematical foundations, imaging systems and their components, image reconstruction and analysis, simulation techniques, and clinical and laboratory applications. The book describes the state of the art of emission tomography, including all facets of conventional SPECT and PET, as well as contemporary topics such as iterative image reconstruction, small-animal imaging, and PET/CT systems. This book is intended as a textbook and reference resource for graduate students, researchers, medical physicists, biomedical engineers, and professional engineers and physicists in the medical-imaging industry. Thorough tutorials of fundamental and advanced topics are presented by dozens of the leading researchers in PET and SPECT. SPECT has long been a mainstay of clinical imaging, and PET is now one of the world's fastest growing medical imaging techniques, owing to its dramatic contributions to cancer imaging and other applications. Emission Tomography: The Fundamentals of PET and SPECT is an essential resource for understanding the technology of SPECT and PET, the most widely used forms of molecular imaging.*Contains thorough tutorial treatments, coupled with coverage of advanced topics*Three of the four holders of the prestigious Institute of Electrical and Electronics Engineers Medical Imaging Scientist Award are chapter contributors*Include color artwork
