Auto-Segmentation for Radiation Oncology

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Publisher : CRC Press
ISBN 13 : 1000376346
Total Pages : 247 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Auto-Segmentation for Radiation Oncology by : Jinzhong Yang

Download or read book Auto-Segmentation for Radiation Oncology written by Jinzhong Yang and published by CRC Press. This book was released on 2021-04-19 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to current state-of-the-art auto-segmentation approaches used in radiation oncology for auto-delineation of organs-of-risk for thoracic radiation treatment planning. Containing the latest, cutting edge technologies and treatments, it explores deep-learning methods, multi-atlas-based methods, and model-based methods that are currently being developed for clinical radiation oncology applications. Each chapter focuses on a specific aspect of algorithm choices and discusses the impact of the different algorithm modules to the algorithm performance as well as the implementation issues for clinical use (including data curation challenges and auto-contour evaluations). This book is an ideal guide for radiation oncology centers looking to learn more about potential auto-segmentation tools for their clinic in addition to medical physicists commissioning auto-segmentation for clinical use. Features: Up-to-date with the latest technologies in the field Edited by leading authorities in the area, with chapter contributions from subject area specialists All approaches presented in this book are validated using a standard benchmark dataset established by the Thoracic Auto-segmentation Challenge held as an event of the 2017 Annual Meeting of American Association of Physicists in Medicine

Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 1441982043
Total Pages : 369 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies by : Ayman S. El-Baz

Download or read book Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies written by Ayman S. El-Baz and published by Springer Science & Business Media. This book was released on 2011-04-11 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Biomedical Image Segmentation

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Publisher : CRC Press
ISBN 13 : 1315355043
Total Pages : 511 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Biomedical Image Segmentation by : Ayman El-Baz

Download or read book Biomedical Image Segmentation written by Ayman El-Baz and published by CRC Press. This book was released on 2016-11-17 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires modality-specific algorithmic treatment. In recent years, substantial progress has been made to biomedical image segmentation. Biomedical image segmentation is characterized by several specific factors. This book presents an overview of the advanced segmentation algorithms and their applications.

Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies

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Publisher : Springer Science & Business Media
ISBN 13 : 1441981950
Total Pages : 415 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies by : Ayman S. El-Baz

Download or read book Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies written by Ayman S. El-Baz and published by Springer Science & Business Media. This book was released on 2011-05-04 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning and Convolutional Neural Networks for Medical Image Computing

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Author :
Publisher : Springer
ISBN 13 : 331942999X
Total Pages : 327 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Deep Learning and Convolutional Neural Networks for Medical Image Computing by : Le Lu

Download or read book Deep Learning and Convolutional Neural Networks for Medical Image Computing written by Le Lu and published by Springer. This book was released on 2017-07-12 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

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Author :
Publisher : Springer Nature
ISBN 13 : 3030139697
Total Pages : 461 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics by : Le Lu

Download or read book Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics written by Le Lu and published by Springer Nature. This book was released on 2019-09-19 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. The book’s chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval. The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.

Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies

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Author :
Publisher : Springer
ISBN 13 : 9781441981950
Total Pages : 410 pages
Book Rating : 4.9/5 (819 download)

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Book Synopsis Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies by : Ayman S. El-Baz

Download or read book Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies written by Ayman S. El-Baz and published by Springer. This book was released on 2011-05-04 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning in Medical Image Analysis

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Author :
Publisher : Springer Nature
ISBN 13 : 3030331288
Total Pages : 184 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Deep Learning in Medical Image Analysis by : Gobert Lee

Download or read book Deep Learning in Medical Image Analysis written by Gobert Lee and published by Springer Nature. This book was released on 2020-02-06 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.

Level Set Method in Medical Imaging Segmentation

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Publisher : CRC Press
ISBN 13 : 135137303X
Total Pages : 396 pages
Book Rating : 4.3/5 (513 download)

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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.

Handbook of Biomedical Image Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 0306486083
Total Pages : 583 pages
Book Rating : 4.3/5 (64 download)

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Book Synopsis Handbook of Biomedical Image Analysis by : David Wilson

Download or read book Handbook of Biomedical Image Analysis written by David Wilson and published by Springer Science & Business Media. This book was released on 2007-04-25 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our goal is to develop automated methods for the segmentation of thr- dimensional biomedical images. Here, we describe the segmentation of c- focal microscopy images of bee brains (20 individuals) by registration to one or several atlas images. Registration is performed by a highly parallel imp- mentation of an entropy-based nonrigid registration algorithm using B-spline transformations. We present and evaluate different methods to solve the cor- spondence problem in atlas based registration. An image can be segmented by registering it to an individual atlas, an average atlas, or multiple atlases. When registering to multiple atlases, combining the individual segmentations into a ?nalsegmentationcanbeachievedbyatlasselection,ormulticlassi?erdecision fusion. Wedescribeallthesemethodsandevaluatethesegmentationaccuracies that they achieve by performing experiments with electronic phantoms as well as by comparing their outputs to a manual gold standard. The present work is focused on the mathematical and computational t- ory behind a technique for deformable image registration termed Hyperelastic Warping, and demonstration of the technique via applications in image regist- tion and strain measurement. The approach combines well-established prin- ples of nonlinear continuum mechanics with forces derived directly from thr- dimensional image data to achieve registration. The general approach does not require the de?nition of landmarks, ?ducials, or surfaces, although it can - commodate these if available. Representative problems demonstrate the robust and ?exible nature of the approach. Three-dimensional registration methods are introduced for registering MRI volumes of the pelvis and prostate. The chapter ?rst reviews the applications, xi xii Preface challenges, and previous methods of image registration in the prostate.

3D Imaging in Medicine

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Publisher : Springer Science & Business Media
ISBN 13 : 3642842119
Total Pages : 449 pages
Book Rating : 4.6/5 (428 download)

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Book Synopsis 3D Imaging in Medicine by : Karl H. Höhne

Download or read book 3D Imaging in Medicine written by Karl H. Höhne and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: The visualization of human anatomy for diagnostic, therapeutic, and educational pur poses has long been a challenge for scientists and artists. In vivo medical imaging could not be introduced until the discovery of X-rays by Wilhelm Conrad ROntgen in 1895. With the early medical imaging techniques which are still in use today, the three-dimensional reality of the human body can only be visualized in two-dimensional projections or cross-sections. Recently, biomedical engineering and computer science have begun to offer the potential of producing natural three-dimensional views of the human anatomy of living subjects. For a broad application of such technology, many scientific and engineering problems still have to be solved. In order to stimulate progress, the NATO Advanced Research Workshop in Travemiinde, West Germany, from June 25 to 29 was organized. It brought together approximately 50 experts in 3D-medical imaging from allover the world. Among the list of topics image acquisition was addressed first, since its quality decisively influences the quality of the 3D-images. For 3D-image generation - in distinction to 2D imaging - a decision has to be made as to which objects contained in the data set are to be visualized. Therefore special emphasis was laid on methods of object definition. For the final visualization of the segmented objects a large variety of visualization algorithms have been proposed in the past. The meeting assessed these techniques.

3D Imaging in Medicine, Second Edition

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Publisher : CRC Press
ISBN 13 : 9780849331794
Total Pages : 394 pages
Book Rating : 4.3/5 (317 download)

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Book Synopsis 3D Imaging in Medicine, Second Edition by : Jayaram K. Udupa

Download or read book 3D Imaging in Medicine, Second Edition written by Jayaram K. Udupa and published by CRC Press. This book was released on 1999-09-28 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to visualize, non-invasively, human internal organs in their true from and shape has intrigued mankind for centuries. While the recent inventions of medical imaging modalities such as computerized tomography and magnetic resonance imaging have revolutionized radiology, the development of three-dimensional (3D) imaging has brought us closer to the age-old quest of non-invasive visualization. The ability to not only visualize but to manipulate and analyze 3D structures from captured multidimensional image data, is vital to a number of diagnostic and therapeutic applications. 3D Imaging in Medicine, Second Edition, unique in its contents, covers both the technical aspects and the actual medical applications of the process in a single source. The value of this technology is obvious. For example, three dimensional imaging allows a radiologist to accurately target the positioning and dosage of chemotherapy as well as to make more accurate diagnoses by showing more pathology; it allows the vascular surgeon to study the flow of blood through clogged arteries; it allows the orthopedist to find all the pieces of a compound fracture; and, it allows oncologists to perform less invasive biopsies. In fact, one of the most important uses of 3D Imaging is in computer-assisted surgery. For example, in cancer surgery, computer images show the surgeon the extent of the tumor so that only the diseased tissue is removed. In short, 3D imaging provides clinicians with information that saves time and money. 3D Imaging in Medicine, Second Edition provides a ready reference on the fundamental science of 3D imaging and its medical applications. The chapters have been written by experts in the field, and the technical aspects are covered in a tutorial fashion, describing the basic principles and algorithms in an easily understandable way. The application areas covered include: surgical planning, neuro-surgery, orthopedics, prosthesis design, brain imaging, analysis of cardio-pulmonary structures, and the assessment of clinical efficacy. The book is designed to provide a quick and systematic understanding of the principles of biomedical visualization to students, scientists and researchers, and to act as a source of information to medical practitioners on a wide variety of clinical applications of 3D imaging.

Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing

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Publisher : CRC Press
ISBN 13 : 1000337138
Total Pages : 181 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing by : Rohit Raja

Download or read book Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing written by Rohit Raja and published by CRC Press. This book was released on 2020-12-23 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field

Computational Modeling of Objects Presented in Images

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Publisher : Springer Science & Business Media
ISBN 13 : 3319040391
Total Pages : 315 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Computational Modeling of Objects Presented in Images by : Paolo Di Giamberardino

Download or read book Computational Modeling of Objects Presented in Images written by Paolo Di Giamberardino and published by Springer Science & Business Media. This book was released on 2014-02-01 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains extended versions of selected papers from the 3rd edition of the International Symposium CompIMAGE. These contributions include cover methods of signal and image processing and analysis to tackle problems found in medicine, material science, surveillance, biometric, robotics, defence, satellite data, traffic analysis and architecture, image segmentation, 2D and 3D reconstruction, data acquisition, interpolation and registration, data visualization, motion and deformation analysis and 3D vision.

Advances in Computational Vision and Medical Image Processing

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Publisher : Springer Science & Business Media
ISBN 13 : 1402090862
Total Pages : 296 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Advances in Computational Vision and Medical Image Processing by : Joao Tavares

Download or read book Advances in Computational Vision and Medical Image Processing written by Joao Tavares and published by Springer Science & Business Media. This book was released on 2008-12-21 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational methodologies of signal processing and imaging analysis, namely considering 2D and 3D images, are commonly used in different applications of the human society. For example, Computational Vision systems are progressively used for surveillance tasks, traf?c analysis, recognition process, inspection p- poses, human-machine interfaces, 3D vision and deformation analysis. One of the main characteristics of the Computational Vision domain is its int- multidisciplinary. In fact, in this domain, methodologies of several more fundam- tal sciences, such as Informatics, Mathematics, Statistics, Psychology, Mechanics and Physics are usually used. Besides this inter-multidisciplinary characteristic, one of the main reasons that contributes for the continually effort done in this domain of the human knowledge is the number of applications in the medical area. For instance, it is possible to consider the use of statistical or physical procedures on medical images in order to model the represented structures. This modeling can have different goals, for example: shape reconstruction, segmentation, registration, behavior interpretation and simulation, motion and deformation analysis, virtual reality, computer-assisted therapy or tissue characterization. The main objective of the ECCOMAS Thematic Conferences on Computational Vision and Medical Image Processing (VIPimage) is to promote a comprehensive forum for discussion on the recent advances in the related ?elds trying to id- tify widespread areas of potential collaboration between researchers of different sciences.

3D Image Processing

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Publisher : Springer Science & Business Media
ISBN 13 : 3642594387
Total Pages : 329 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis 3D Image Processing by : D. Caramella

Download or read book 3D Image Processing written by D. Caramella and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Few fields have witnessed such impressive advances as the application of computer technology to radiology. The progress achieved has revolutionized diagnosis and greatly facilitated treatment selection and accurate planning of procedures. This book, written by leading experts from many different countries, provides a comprehensive and up-to-date overview of the role of 3D image processing. The first section covers a wide range of technical aspects in an informative way. This is followed by the main section, in which the principal clinical applications are described and discussed in depth. To complete the picture, the final section focuses on recent developments in functional imaging and computer-aided surgery. This book will prove invaluable to all who have an interest in this complex but vitally important field.

3D Imaging in Medicine, Second Edition

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Publisher : CRC Press
ISBN 13 : 1351470302
Total Pages : 362 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis 3D Imaging in Medicine, Second Edition by : Jayaram K. Udupa

Download or read book 3D Imaging in Medicine, Second Edition written by Jayaram K. Udupa and published by CRC Press. This book was released on 2023-08-18 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a quick and systematic presentation of the principles of biomedical visualization and three-dimensional (3D) imaging. Topics discussed include basic principles and algorithms, surgical planning, neurosurgery, orthopedics, prosthesis design, brain imaging, cardio-pulmonary structure analysis and the assessment of clinical efficacy. Students, scientists, researchers, and radiologists will find 3D Imaging in Medicine a valuable source of information for a variety of actual and potential clinical applications for 3-D imaging.