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Statistics of Medical Imaging

Author: Tianhu Lei

Publisher: CRC Press

Published: 2011-12-19

Total Pages: 426

ISBN-13: 1420088432

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.

Biostatistics for Radiologists

Author: Francesco Sardanelli

Publisher: Springer Science & Business Media

Published: 2009-03-31

Total Pages: 244

ISBN-13: 8847011337

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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".

Riemannian Geometric Statistics in Medical Image Analysis

Author: Xavier Pennec

Publisher: Academic Press

Published: 2019-09-02

Total Pages: 636

ISBN-13: 0128147261

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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

Big Data in Multimodal Medical Imaging

Author: Ayman El-Baz

Publisher: CRC Press

Published: 2019-11-05

Total Pages: 330

ISBN-13: 1351380737

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There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.

Medical Imaging Systems

Author: Andreas Maier

Publisher: Springer

Published: 2018-08-02

Total Pages: 263

ISBN-13: 3319965204

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This open access book gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. The authors of the book first explain the foundations of system theory and image processing, before highlighting several modalities in a dedicated chapter. The initial focus is on modalities that are closely related to traditional camera systems such as endoscopy and microscopy. This is followed by more complex image formation processes: magnetic resonance imaging, X-ray projection imaging, computed tomography, X-ray phase-contrast imaging, nuclear imaging, ultrasound, and optical coherence tomography.

Big Data in Medical Image Processing

Author: R. Suganya

Publisher: CRC Press

Published: 2018-01-29

Total Pages: 202

ISBN-13: 1351366629

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The field of medical imaging seen rapid development over the last two decades and has consequently revolutionized the way in which modern medicine is practiced. Diseases and their symptoms are constantly changing therefore continuous updating is necessary for the data to be relevant. Diseases fall into different categories, even a small difference in symptoms may result in categorising it in a different group altogether. Thus analysing data accurately is of critical importance. This book concentrates on diagnosing diseases like cancer or tumor from different modalities of images. This book is divided into the following domains: Importance of big data in medical imaging, pre-processing, image registration, feature extraction, classification and retrieval. It is further supplemented by the medical analyst for a continuous treatment process. The book provides an automated system that could retrieve images based on user’s interest to a point of providing decision support. It will help medical analysts to take informed decisions before planning treatment and surgery. It will also be useful to researchers who are working in problems involved in medical imaging.

Manual of Diagnostic Ultrasound

Author: World Health Organization

Publisher: World Health Organization

Published: 1995

Total Pages: 354

ISBN-13: 9241544619

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A didactic, illustrated guide to the use of ultrasound as a diagnostic tool in clinical practice. Prepared by an international group of experts with wide experience in both developed and developing countries, the manual responds to the need for a basic reference text that can help doctors, sonographers, nurses, and midwives solve imaging problems when no experts are available. With this need in mind, the manual adopts a practical approach aimed at providing a thorough grounding in both the techniques of ultrasound and the interpretation of images. The need for extensive supervised training is repeatedly emphasized. Because the clinical value of ultrasound depends so greatly on the experience and skill of the operator, the manual makes a special effort to alert readers to common pitfalls and errors, and to indicate specific clinical situations where ultrasound may not be helpful or reliable as a diagnostic tool. Explanatory text is supported by numerous practical tips, warnings, checklists and over 600 illustrations. The opening chapters explain how ultrasound works, outline the factors to consider when choosing a scanner, and introduce the basic rules of scanning, including advice on how to recognize and interpret artefacts. Guidance on the selection of ultrasound equipment includes clear advice concerning where costs can be spared and where investment is essential. The core of the manual consists of seventeen chapters providing guidance on scanning techniques and the interpretation of images for specific organs and anatomical sites, with the most extensive chapter devoted to obstetrics. Each chapter contains illustrated information on indications for scanning, preparation of the patient, including choice of transducer and setting of the correct gain, general scanning techniques, and specific techniques for identifying anatomical landmarks and recognizing abnormalities. The manual concludes with WHO specifications for a general purpose scanner judged entirely suitable for 90-95% of the most common ultrasound examinations.

Medical Imaging Informatics

Author: Alex A.T. Bui

Publisher: Springer Science & Business Media

Published: 2009-12-01

Total Pages: 454

ISBN-13: 1441903852

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Medical Imaging Informatics provides an overview of this growing discipline, which stems from an intersection of biomedical informatics, medical imaging, computer science and medicine. Supporting two complementary views, this volume explores the fundamental technologies and algorithms that comprise this field, as well as the application of medical imaging informatics to subsequently improve healthcare research. Clearly written in a four part structure, this introduction follows natural healthcare processes, illustrating the roles of data collection and standardization, context extraction and modeling, and medical decision making tools and applications. Medical Imaging Informatics identifies core concepts within the field, explores research challenges that drive development, and includes current state-of-the-art methods and strategies.

Artificial Intelligence in Medical Imaging

Author: Erik R. Ranschaert

Publisher: Springer

Published: 2019-01-29

Total Pages: 373

ISBN-13: 3319948784

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This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Quantitative Analysis in Nuclear Medicine Imaging

Author: Habib Zaidi

Publisher: Springer Science & Business Media

Published: 2006-07-11

Total Pages: 593

ISBN-13: 0387254447

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This book provides a review of image analysis techniques as they are applied in the field of diagnostic and therapeutic nuclear medicine. Driven in part by the remarkable sophistication of nuclear medicine instrumentation and - crease in computing power and its ready and inexpensive availability, this is a relatively new yet rapidly expanding field. Likewise, although the use of nuclear imaging for diagnosis and therapy has origins dating back almost to the pioneering work of Dr G. de Hevesy, quantitative imaging has only recently emerged as a promising approach for diagnosis and therapy of many diseases. An effort has, therefore, been made to place the reviews provided in this book in a broader context. The effort to do this is reflected by the inclusion of introductory chapters that address basic principles of nuclear medicine instrumentation and dual-modality imaging, followed by overview of issues that are closely related to quantitative nuclear imaging and its potential role in diagnostic and therapeutic applications. A brief overview of each chapter is provided below. Chapter 1 presents a general overview of nuclear medicine imaging physics and instrumentation including planar scintigraphy, single-photon emission computed tomography (SPECT) and positron emission tomography (PET). Nowadays, patients’ diagnosis and therapy is rarely done without the use of imaging technology. As such, imaging considerations are incorporated in almost every chapter of the book. The development of dual-modality - aging systems is an emerging research field, which is addressed in chapter 2.