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Med-books.by - Библиотека медицинской литературы » Медицинская информатика

Introduction to the Principles of Medical Imaging - Guy Ch., Ffytche D. - 2005 год



Introduction to the Principles of Medical Imaging - Guy Ch., Ffytche D. - 2005 год

The introduction of X-ray computed tomography (CT) 25 years ago revolutionized medical imaging; X-ray CT itself provided the first clear cross-sectional images of the human body, with substantial contrast between different types of soft tissue. The enduring legacy of CT is, however, the spur that it gave to the subsequent introduction of tomographic imaging techniques into diagnostic nuclear medicine and the extraordinarily rapid development of magnetic resonance imaging (MRI) over this period.
This book is a non-mathematical introduction to the principles underlying modern medical imaging, taking tomography as its central theme. The first three chapters cover the general principles of tomography, a survey of the atomic and nuclear physics which underpins modern imaging, and a review of the key issues involved in radiation protection. The subsequent chapters deal in turn with X-ray radiography, gamma imaging, MRI and ultrasound. The clinical role of diagnostic imaging is illustrated in the final chapter through the use of fictional clinical histories. Three appendices provide a more mathematical background to the tomographic method, the principles of mathematical Fourier methods, and the mathematics of MRI. This revised edition includes new introductory sections on the relevant physics of molecules in general, and water, in particular. Every chapter now has a table of key points with cross-references to other sections. Several figures have also been revised.

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Digital Signal Processing for Medical Imaging Using Matlab - Gopi E.S. - 2013 год



Digital Signal Processing for Medical Imaging Using Matlab - Gopi E.S. - 2013 год

Digital signal processing (DSP) techniques, like Radon transformation, Projection techniques, Fourier transformation in polar form, Hankel transformation, etc., are used in Medical imaging techniques like Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) during the process of imaging. These are not usually covered in the regular DSP and Image processing books. This book is written with the intention to focus the DSP aspects used during the process of imaging in CT and MRI. Also, DSP aspects used in the post imaging techniques such as Image enhancement, Image compression and pattern recognition are also discussed in this book. The Matlab illustrations are given for better understanding. This book is suitable for beginners who are doing research in Medical imaging processing.

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Biomedical Image Analysis and Machine Learning Technologies. Applications and Techniques - Gonzalez F.A., Romero E. - 2010 год



Biomedical Image Analysis and Machine Learning Technologies. Applications and Techniques - Gonzalez F.A., Romero E. - 2010 год

This book is concerned with a machine learning approach to analyze and understand biomedical images. The development of medical imaging technologies in the last three decades has been truly revolutionary, while in parallel, machine learning has experienced a vertiginous advance in recent years. Several challenging problems in the biomedical domain and the set of powerful machine learning techniques have resulted in a new domain on its own, where the power and beauty of these techniques can be fully exploited to obtain proper solutions to these challenges. The main goal of the book is to highlight the great research potential of this interdisciplinary area, providing insights on new potential applications of machine learning techniques to the solution of important problems in biomedical image applications.
The prime intended audience of the book corresponds to researchers in both biomedical imaging and machine learning. Biomedical imaging researchers, as well as practitioners will find insights on how to adapt/apply machine learning techniques to tackle challenging image analysis problems. Also the book will provide useful material for machine learning researchers looking for interesting application problems. The book also provides material for supporting advanced undergrad and graduate courses on biomedical image analysis and/or machine learning.

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Two-Dimensional Real-Time Ultrasonic Imaging of the Heart - Giuliani E.R. - 1985 год - 412 с.



Two-Dimensional Real-Time Ultrasonic Imaging of the Heart - Giuliani E.R. - 1985 год - 412 с.

In the evaluation of patients who have or are suspected to have cardiac disease, the use of ultrasound is now an established and widely accepted approach. Since its modest beginning three decades ago, the technique of echocardiography developed rapidly. This success can be credited to the cooperation between the worlds of medicine and industry. Recognizing the potential clinical utility of this technique, equipment companies developed better and better instrumentation, and with competition came a leveling of the costs of this instrumentation. We hope that the future will bring not only continued improvement in technology but also a continued decrease in cost.

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Imaging in Percutaneous Musculoskeletal Interventions - Gangi A., Guth S., Guermazi A. - 2009 год



Imaging in Percutaneous Musculoskeletal Interventions - Gangi A., Guth S., Guermazi A. - 2009 год

This is one of the first books to deal specifically with imaging in percutaneous musculoskeletal interventions. The use of different imaging modalities during these procedures is well described. In the first chapter, the basic procedures and different guidance techniques are presented and discussed. The ensuing chapters describe in exhaustive detail the abilities and uses of imaging in guiding procedures ranging from biopsy and joint injection to management of pain and tumors. These procedures are extensively documented in adults as well as in the pediatric population. The third part of the book describes the different indications for vascular interventions in musculoskeletal lesions. The final chapter focuses on ultrasound-guided interventions, as they are more common and tend to be fashionable. The book is well illustrated with carefully chosen and technically excellent images. Each of the 18 chapters is written by an expert of international repute, making this book the most current and complete treatment of the subject available. It should be of great interest to interventional radiologists and also musculoskeletal and general radiologists.

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The Mathematics of Medical Imaging: A Beginner's Guide - Feeman T.G. - 2009 год - 151 с.



The Mathematics of Medical Imaging: A Beginner's Guide - Feeman T.G. - 2009 год - 151 с.

This text explores medical imaging, one of the most significant areas of recent mathematical applications, in a concise manner accessible to undergraduate students. The author emphasizes the mathematical aspects of medical imaging, including not only the theoretical background, but also the role of approximation methods and the computer implementation of the inversion algorithms. In twenty-first century health care, CAT scans, ultrasounds, and MRIs are commonplace. Significant computational advances, along with the development, design, and improvement of the machines themselves, can only occur in conjunction with a proper understanding of the mathematics. This book is inherently interdisciplinary in nature, and therefore is appropriate for students of engineering, physics, and computer science, in addition to mathematics.

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Medical Imaging in Clinical Practice - Erondu O.F. - 2013 год - 362 с.



Medical Imaging in Clinical Practice - Erondu O.F. - 2013 год - 362 с.

This book is a compendium of the various applications of imaging modalities in specific clinical conditions. It captures in an easy to read manner, the experiences of various experts drawn from across the globe. It explores the conventional techniques, advanced modalities and on going research efforts in the ever widening horizon of medical imaging.
The various topics would be relevant to residents, radiologists and specialists who order and interpret various medical imaging procedures. It is an essential for the inquisitive mind, seeking to understand the scope of medical imaging in clinical practice.

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Introduction to the mathematics of medical imaging - Epstein C.L. - 2008 год - 793 с.



Introduction to the mathematics of medical imaging - Epstein C.L. - 2008 год - 793 с.

The target audience for this book is junior or senior math undergraduates with a firm command of multi-variable calculus, linear algebra over the real and complex numbers, and the basic facts of mathematical analysis. Some familiarity with basic physics would also be useful. The book is written in the language of mathematics, which, as I have learned, is quite distinct from the language of physics or the language of engineering. Nonetheless, the discussion of every topic begins at an elementary level and the book should, with a little translation, be usable by advanced science and engineering students with some mathematical sophistication. A large part of the mathematical background material is provided in two appendices.

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Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies - El-Baz A.S., U R.A., Mirmehdi M., Suri J.S. - 2011 год



Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies - El-Baz A.S., U R.A., Mirmehdi M., Suri J.S. - 2011 год

With the advances in image guided surgery for cancer treatment, the role of image segmentation and registration has become very critical. The central engine of any image guided surgery product is its ability to quantify the organ or segment the organ whether it is a magnetic resonance imaging (MRI) and computed tomography (CT), X-ray, PET, SPECT, Ultrasound, and Molecular imaging modality. Sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures present in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning system designs. The focus of this book in towards the state of the art techniques in the area of image segmentation and registration.
Segmentation of medical images in 2-D, 3-D, and 4-D has taken new dimension. This is mainly because for real-time image guidance in diagnosis and therapeutics. The application of image/volume registration is prominently seen in reconstruction, multimodality fusion, and now propagating in atlas-based analysis. The focus of this book is to share the application of combined segmentation and registration in medical imaging.

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Biomedical Image Segmentation. Advances and Trends - EI-Baz A., Jiang X., Suri J.S. - 2017 год - 556 с.



Biomedical Image Segmentation. Advances and Trends - EI-Baz A., Jiang X., Suri J.S. - 2017 год - 556 с.

Medical imaging is an indispensable tool for patients’ healthcare in modern medicine. It is considered to be one of the basic monitoring tools—today’s medical imaging effectively assists clinicians and radiologists in diagnosing diseases, making therapeutic or surgical decisions, and guiding surgery operations. Recent advances in medical imaging modalities provide images with a menagerie of sizes, structures, resolution, and degrees of contrast. A two-dimensional (2D) image is a rectangular array of pixels containing measured scalar or vectorial visual signals (e.g., intensities or colors), which quantify properties of related spatial locations in a whole body or its part. The 2D image of a thin planar cross-section of a 3D object is usually called a slice. A collection of successive slices forms a 3D image, which is an array of voxels.

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