Statistics In Imaging Sciences

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Statistics for Imaging, Optics, and Photonics

Author : Peter Bajorski
Publisher : John Wiley & Sons
ISBN 13 : 0470509457
Total Pages : 420 pages
Book Rating : 4.4/5 (75 download)

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Book Synopsis Statistics for Imaging, Optics, and Photonics by : Peter Bajorski

Download or read book Statistics for Imaging, Optics, and Photonics written by Peter Bajorski and published by John Wiley & Sons. This book was released on 2011-10-17 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: A vivid, hands-on discussion of the statistical methods in imaging, optics, and photonics applications In the field of imaging science, there is a growing need for students and practitioners to be equipped with the necessary knowledge and tools to carry out quantitative analysis of data. Providing a self-contained approach that is not too heavily statistical in nature, Statistics for Imaging, Optics, and Photonics presents necessary analytical techniques in the context of real examples from various areas within the field, including remote sensing, color science, printing, and astronomy. Bridging the gap between imaging, optics, photonics, and statistical data analysis, the author uniquely concentrates on statistical inference, providing a wide range of relevant methods. Brief introductions to key probabilistic terms are provided at the beginning of the book in order to present the notation used, followed by discussions on multivariate techniques such as: Linear regression models, vector and matrix algebra, and random vectors and matrices Multivariate statistical inference, including inferences about both mean vectors and covariance matrices Principal components analysis Canonical correlation analysis Discrimination and classification analysis for two or more populations and spatial smoothing Cluster analysis, including similarity and dissimilarity measures and hierarchical and nonhierarchical clustering methods Intuitive and geometric understanding of concepts is emphasized, and all examples are relatively simple and include background explanations. Computational results and graphs are presented using the freely available R software, and can be replicated by using a variety of software packages. Throughout the book, problem sets and solutions contain partial numerical results, allowing readers to confirm the accuracy of their approach; and a related website features additional resources including the book's datasets and figures. Statistics for Imaging, Optics, and Photonics is an excellent book for courses on multivariate statistics for imaging science, optics, and photonics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for professionals working in imaging, optics, and photonics who carry out data analyses in their everyday work.

STATISTICS IN IMAGING SCIENCES

Author :
Publisher :
ISBN 13 : 9783540303305
Total Pages : 300 pages
Book Rating : 4.3/5 (33 download)

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Book Synopsis STATISTICS IN IMAGING SCIENCES by :

Download or read book STATISTICS IN IMAGING SCIENCES written by and published by . This book was released on 2009-01-31 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical and Computational Methods in Brain Image Analysis

Author : Moo K. Chung
Publisher : CRC Press
ISBN 13 : 1439836353
Total Pages : 436 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Statistical and Computational Methods in Brain Image Analysis by : Moo K. Chung

Download or read book Statistical and Computational Methods in Brain Image Analysis written by Moo K. Chung and published by CRC Press. This book was released on 2013-07-23 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLAB® and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author’s website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics.

Natural Image Statistics

Author : Aapo Hyvärinen
Publisher : Springer Science & Business Media
ISBN 13 : 1848824912
Total Pages : 450 pages
Book Rating : 4.8/5 (488 download)

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Book Synopsis Natural Image Statistics by : Aapo Hyvärinen

Download or read book Natural Image Statistics written by Aapo Hyvärinen and published by Springer Science & Business Media. This book was released on 2009-04-21 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aims and Scope This book is both an introductory textbook and a research monograph on modeling the statistical structure of natural images. In very simple terms, “natural images” are photographs of the typical environment where we live. In this book, their statistical structure is described using a number of statistical models whose parameters are estimated from image samples. Our main motivation for exploring natural image statistics is computational m- eling of biological visual systems. A theoretical framework which is gaining more and more support considers the properties of the visual system to be re?ections of the statistical structure of natural images because of evolutionary adaptation processes. Another motivation for natural image statistics research is in computer science and engineering, where it helps in development of better image processing and computer vision methods. While research on natural image statistics has been growing rapidly since the mid-1990s, no attempt has been made to cover the ?eld in a single book, providing a uni?ed view of the different models and approaches. This book attempts to do just that. Furthermore, our aim is to provide an accessible introduction to the ?eld for students in related disciplines.

Research for Medical Imaging and Radiation Sciences

Author : Euclid Seeram
Publisher : Springer Nature
ISBN 13 : 3030799565
Total Pages : 215 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Research for Medical Imaging and Radiation Sciences by : Euclid Seeram

Download or read book Research for Medical Imaging and Radiation Sciences written by Euclid Seeram and published by Springer Nature. This book was released on 2022-01-03 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses essential principles of research according to the scientific method for medical imaging technology research. The scope of this book covers the nature of scientific research; quantitative and qualitative approaches essentials; research planning; literature review fundamentals; research methods; data collection, analysis, and interpretation; and communicating research findings. The book meets the educational requirements on Research Principles and Concepts (for entry to practice) of the following professional radiologic technology associations: the American Society of Radiologic Technologists (ASRT), the Canadian Association of Medical Radiation Technologists (CAMRT), the College of Radiographers in the United Kingdom, and radiography societies and associations in Asia, Australia, Europe, and Africa. This is an ideal book for radiologic technologists, nuclear medicine technologists, and radiation therapists seeking to get started in research in their profession. Additionally, biomedical imaging engineering technologists, radiologists, and medical imaging physicists may use this as a “guiding principles” textbook.

Biostatistics for Radiologists

Author : Francesco Sardanelli
Publisher : Springer Science & Business Media
ISBN 13 : 8847011337
Total Pages : 244 pages
Book Rating : 4.8/5 (47 download)

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Book Synopsis Biostatistics for Radiologists by : Francesco Sardanelli

Download or read book Biostatistics for Radiologists written by Francesco Sardanelli and published by Springer Science & Business Media. This book was released on 2009-03-31 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to present statistical problems and methods in a friendly way to radiologists, emphasizing statistical issues and methods most frequently used in radiological studies (e.g., nonparametric tests, analysis of intra- and interobserver reproducibility, comparison of sensitivity and specificity among different imaging modality, difference between clinical and screening application of diagnostic tests, ect.). The tests will be presented starting from a radiological "problem" and all examples of statistical methods applications will be "radiological".

Statistics for Imaging, Optics, and Photonics

Author : Peter Bajorski
Publisher : John Wiley & Sons
ISBN 13 : 1118121945
Total Pages : 420 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Statistics for Imaging, Optics, and Photonics by : Peter Bajorski

Download or read book Statistics for Imaging, Optics, and Photonics written by Peter Bajorski and published by John Wiley & Sons. This book was released on 2011-09-26 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: A vivid, hands-on discussion of the statistical methods in imaging, optics, and photonics applications In the field of imaging science, there is a growing need for students and practitioners to be equipped with the necessary knowledge and tools to carry out quantitative analysis of data. Providing a self-contained approach that is not too heavily statistical in nature, Statistics for Imaging, Optics, and Photonics presents necessary analytical techniques in the context of real examples from various areas within the field, including remote sensing, color science, printing, and astronomy. Bridging the gap between imaging, optics, photonics, and statistical data analysis, the author uniquely concentrates on statistical inference, providing a wide range of relevant methods. Brief introductions to key probabilistic terms are provided at the beginning of the book in order to present the notation used, followed by discussions on multivariate techniques such as: Linear regression models, vector and matrix algebra, and random vectors and matrices Multivariate statistical inference, including inferences about both mean vectors and covariance matrices Principal components analysis Canonical correlation analysis Discrimination and classification analysis for two or more populations and spatial smoothing Cluster analysis, including similarity and dissimilarity measures and hierarchical and nonhierarchical clustering methods Intuitive and geometric understanding of concepts is emphasized, and all examples are relatively simple and include background explanations. Computational results and graphs are presented using the freely available R software, and can be replicated by using a variety of software packages. Throughout the book, problem sets and solutions contain partial numerical results, allowing readers to confirm the accuracy of their approach; and a related website features additional resources including the book's datasets and figures. Statistics for Imaging, Optics, and Photonics is an excellent book for courses on multivariate statistics for imaging science, optics, and photonics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for professionals working in imaging, optics, and photonics who carry out data analyses in their everyday work.

Mathematical and Statistical Methods for Multistatic Imaging

Author : Habib Ammari
Publisher : Springer
ISBN 13 : 3319025856
Total Pages : 366 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Mathematical and Statistical Methods for Multistatic Imaging by : Habib Ammari

Download or read book Mathematical and Statistical Methods for Multistatic Imaging written by Habib Ammari and published by Springer. This book was released on 2013-11-29 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent mathematical, numerical, and statistical approaches for multistatic imaging of targets with waves at single or multiple frequencies. The waves can be acoustic, elastic or electromagnetic. They are generated by point sources on a transmitter array and measured on a receiver array. An important problem in multistatic imaging is to quantify and understand the trade-offs between data size, computational complexity, signal-to-noise ratio, and resolution. Another fundamental problem is to have a shape representation well suited to solving target imaging problems from multistatic data. In this book the trade-off between resolution and stability when the data are noisy is addressed. Efficient imaging algorithms are provided and their resolution and stability with respect to noise in the measurements analyzed. It also shows that high-order polarization tensors provide an accurate representation of the target. Moreover, a dictionary-matching technique based on new invariants for the generalized polarization tensors is introduced. Matlab codes for the main algorithms described in this book are provided. Numerical illustrations using these codes in order to highlight the performance and show the limitations of numerical approaches for multistatic imaging are presented.

The Statistical Analysis of Functional MRI Data

Author : Nicole Lazar
Publisher : Springer Science & Business Media
ISBN 13 : 0387781919
Total Pages : 302 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis The Statistical Analysis of Functional MRI Data by : Nicole Lazar

Download or read book The Statistical Analysis of Functional MRI Data written by Nicole Lazar and published by Springer Science & Business Media. This book was released on 2008-06-10 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of brain function is one of the most fascinating pursuits of m- ern science. Functional neuroimaging is an important component of much of the current research in cognitive, clinical, and social psychology. The exci- ment of studying the brain is recognized in both the popular press and the scienti?c community. In the pages of mainstream publications, including The New York Times and Wired, readers can learn about cutting-edge research into topics such as understanding how customers react to products and - vertisements (“If your brain has a ‘buy button,’ what pushes it?”, The New York Times,October19,2004),howviewersrespondtocampaignads(“Using M. R. I. ’s to see politics on the brain,” The New York Times, April 20, 2004; “This is your brain on Hillary: Political neuroscience hits new low,” Wired, November 12,2007),howmen and womenreactto sexualstimulation (“Brain scans arouse researchers,”Wired, April 19, 2004), distinguishing lies from the truth (“Duped,” The New Yorker, July 2, 2007; “Woman convicted of child abuse hopes fMRI can prove her innocence,” Wired, November 5, 2007), and even what separates “cool” people from “nerds” (“If you secretly like Michael Bolton, we’ll know,” Wired, October 2004). Reports on pathologies such as autism, in which neuroimaging plays a large role, are also common (for - stance, a Time magazine cover story from May 6, 2002, entitled “Inside the world of autism”).

Riemannian Geometric Statistics in Medical Image Analysis

Author : Xavier Pennec
Publisher : Academic Press
ISBN 13 : 0128147261
Total Pages : 636 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Riemannian Geometric Statistics in Medical Image Analysis by : Xavier Pennec

Download or read book Riemannian Geometric Statistics in Medical Image Analysis written by Xavier Pennec and published by Academic Press. This book was released on 2019-09-02 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a presentation of state-of-the-art methods. Beyond medical image computing, the methods described in this book may also apply to other domains such as signal processing, computer vision, geometric deep learning, and other domains where statistics on geometric features appear. As such, the presented core methodology takes its place in the field of geometric statistics, the statistical analysis of data being elements of nonlinear geometric spaces. The foundational material and the advanced techniques presented in the later parts of the book can be useful in domains outside medical imaging and present important applications of geometric statistics methodology Content includes: - The foundations of Riemannian geometric methods for statistics on manifolds with emphasis on concepts rather than on proofs - Applications of statistics on manifolds and shape spaces in medical image computing - Diffeomorphic deformations and their applications As the methods described apply to domains such as signal processing (radar signal processing and brain computer interaction), computer vision (object and face recognition), and other domains where statistics of geometric features appear, this book is suitable for researchers and graduate students in medical imaging, engineering and computer science. - A complete reference covering both the foundations and state-of-the-art methods - Edited and authored by leading researchers in the field - Contains theory, examples, applications, and algorithms - Gives an overview of current research challenges and future applications

Machine Learning and Medical Imaging

Author : Guorong Wu
Publisher : Academic Press
ISBN 13 : 0128041145
Total Pages : 514 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Machine Learning and Medical Imaging by : Guorong Wu

Download or read book Machine Learning and Medical Imaging written by Guorong Wu and published by Academic Press. This book was released on 2016-08-11 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. - Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems - Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics - Features self-contained chapters with a thorough literature review - Assesses the development of future machine learning techniques and the further application of existing techniques

Statistical Image Processing and Multidimensional Modeling

Author : Paul Fieguth
Publisher : Springer Science & Business Media
ISBN 13 : 1441972943
Total Pages : 465 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Statistical Image Processing and Multidimensional Modeling by : Paul Fieguth

Download or read book Statistical Image Processing and Multidimensional Modeling written by Paul Fieguth and published by Springer Science & Business Media. This book was released on 2010-10-17 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something—an artery, a road, a DNA marker, an oil spill—from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over a two or higher dimensional space, and to which standard image-processing algorithms may not apply. There are many important data analysis methods developed in this text for such statistical image problems. Examples abound throughout remote sensing (satellite data mapping, data assimilation, climate-change studies, land use), medical imaging (organ segmentation, anomaly detection), computer vision (image classification, segmentation), and other 2D/3D problems (biological imaging, porous media). The goal, then, of this text is to address methods for solving multidimensional statistical problems. The text strikes a balance between mathematics and theory on the one hand, versus applications and algorithms on the other, by deliberately developing the basic theory (Part I), the mathematical modeling (Part II), and the algorithmic and numerical methods (Part III) of solving a given problem. The particular emphases of the book include inverse problems, multidimensional modeling, random fields, and hierarchical methods.

Statistics of Medical Imaging

Author : Tianhu Lei
Publisher : CRC Press
ISBN 13 : 1420088432
Total Pages : 426 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Statistics of Medical Imaging by : Tianhu Lei

Download or read book Statistics of Medical Imaging written by Tianhu Lei and published by CRC Press. This book was released on 2011-12-19 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: More work is being done in the statistical aspects of medical imaging, and this book fills the gap to provide a unified framework of study by presenting a complete look at medical imaging and statistics - from the statistical aspects of imaging technology to the statistical analysis of images. It provides technicians and students with the statistical principles that underlay medical imaging, as required reference material for researchers involved in the design of new technology. Illustrations are included throughout as are many real examples, and algorithms. The text also includes exercises developed out of the author's many years experience with studying the statistics of medical imaging.

Statistical and Computational Methods in Brain Image Analysis

Author : Moo K. Chung
Publisher :
ISBN 13 : 9780429094323
Total Pages : 400 pages
Book Rating : 4.0/5 (943 download)

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Book Synopsis Statistical and Computational Methods in Brain Image Analysis by : Moo K. Chung

Download or read book Statistical and Computational Methods in Brain Image Analysis written by Moo K. Chung and published by . This book was released on 2014 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLAB? and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author's website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics."--

Handbook of Neuroimaging Data Analysis

Author : Hernando Ombao
Publisher : CRC Press
ISBN 13 : 1482220989
Total Pages : 702 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Handbook of Neuroimaging Data Analysis by : Hernando Ombao

Download or read book Handbook of Neuroimaging Data Analysis written by Hernando Ombao and published by CRC Press. This book was released on 2016-11-18 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.

Hyperspectral Imaging

Author :
Publisher : Elsevier
ISBN 13 : 0444639780
Total Pages : 802 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Hyperspectral Imaging by :

Download or read book Hyperspectral Imaging written by and published by Elsevier. This book was released on 2019-09-29 with total page 802 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral Imaging, Volume 32, presents a comprehensive exploration of the different analytical methodologies applied on hyperspectral imaging and a state-of-the-art analysis of applications in different scientific and industrial areas. This book presents, for the first time, a comprehensive collection of the main multivariate algorithms used for hyperspectral image analysis in different fields of application. The benefits, drawbacks and suitability of each are fully discussed, along with examples of their application. Users will find state-of-the art information on the machinery for hyperspectral image acquisition, along with a critical assessment of the usage of hyperspectral imaging in diverse scientific fields. - Provides a comprehensive roadmap of hyperspectral image analysis, with benefits and considerations for each method discussed - Covers state-of-the-art applications in different scientific fields - Discusses the implementation of hyperspectral devices in different environments

Foundations of Image Science

Author : Harrison H. Barrett
Publisher : John Wiley & Sons
ISBN 13 : 1118772776
Total Pages : 1857 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Foundations of Image Science by : Harrison H. Barrett

Download or read book Foundations of Image Science written by Harrison H. Barrett and published by John Wiley & Sons. This book was released on 2013-06-13 with total page 1857 pages. Available in PDF, EPUB and Kindle. Book excerpt: Winner of the 2006 Joseph W. Goodman Book Writing Award! A comprehensive treatment of the principles, mathematics, and statistics of image science In today's visually oriented society, images play an important role in conveying messages. From seismic imaging to satellite images to medical images, our modern society would be lost without images to enhance our understanding of our health, our culture, and our world. Foundations of Image Science presents a comprehensive treatment of the principles, mathematics, and statistics needed to understand and evaluate imaging systems. The book is the first to provide a thorough treatment of the continuous-to-discrete, or CD, model of digital imaging. Foundations of Image Science emphasizes the need for meaningful, objective assessment of image quality and presents the necessary tools for this purpose. Approaching the subject within a well-defined theoretical and physical context, this landmark text presents the mathematical underpinnings of image science at a level that is accessible to graduate students and practitioners working with imaging systems, as well as well-motivated undergraduate students. Destined to become a standard text in the field, Foundations of Image Science covers: Mathematical Foundations: Examines the essential mathematical foundations of image science Image Formation–Models and Mechanisms: Presents a comprehensive and unified treatment of the mathematical and statistical principles of imaging, with an emphasis on digital imaging systems and the use of SVD methods Image Quality: Provides a systematic exposition of the methodology for objective or task-based assessment of image quality Applications: Presents detailed case studies of specific direct and indirect imaging systems and provides examples of how to apply the various mathematical tools covered in the book Appendices: Covers the prerequisite material necessary for understanding the material in the main text, including matrix algebra, complex variables, and the basics of probability theory