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Author: Stephen T.C. Wong
Publisher: Springer Science & Business Media
ISBN: 1461555531
Category : Medical
Languages : en
Pages : 405
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Book Description
Medical Image Databases covers the new technologies of biomedical imaging databases and their applications in clinical services, education, and research. Authors were selected because they are doing cutting-edge basic or technology work in relevant areas. This was done to infuse each chapter with ideas from people actively investigating and developing medical image databases rather than simply review the existing literature. The authors have analyzed the literature and have expanded on their own research. They have also addressed several common threads within their generic topics. These include system architecture, standards, information retrieval, data modeling, image visualizations, query languages, telematics, data mining, and decision supports. The new ideas and results reported in this volume suggest new and better ways to develop imaging databases and possibly lead us to the next information infrastructure in biomedicine. Medical Image Databases is suitable as a textbook for a graduate-level course on biomedical imaging or medical image databases, and as a reference for researchers and practitioners in industry.
Author: Stephen T.C. Wong
Publisher: Springer Science & Business Media
ISBN: 1461555531
Category : Medical
Languages : en
Pages : 405
Get Book Here
Book Description
Medical Image Databases covers the new technologies of biomedical imaging databases and their applications in clinical services, education, and research. Authors were selected because they are doing cutting-edge basic or technology work in relevant areas. This was done to infuse each chapter with ideas from people actively investigating and developing medical image databases rather than simply review the existing literature. The authors have analyzed the literature and have expanded on their own research. They have also addressed several common threads within their generic topics. These include system architecture, standards, information retrieval, data modeling, image visualizations, query languages, telematics, data mining, and decision supports. The new ideas and results reported in this volume suggest new and better ways to develop imaging databases and possibly lead us to the next information infrastructure in biomedicine. Medical Image Databases is suitable as a textbook for a graduate-level course on biomedical imaging or medical image databases, and as a reference for researchers and practitioners in industry.
Author: Vittorio Castelli
Publisher: John Wiley & Sons
ISBN: 0471464074
Category : Computers
Languages : en
Pages : 609
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Book Description
The explosive growth of multimedia data transmission has generated a critical need for efficient, high-capacity image databases, as well as powerful search engines to retrieve image data from them. This book brings together contributions by an international all-star team of innovators in the field who share their insights into all key aspects of image database and search engine construction. Readers get in-depth discussions of the entire range of crucial image database architecture, indexing and retrieval, transmission, display, and user interface issues. And, using examples from an array of disciplines, the authors present cutting-edge applications in medical imagery, multimedia communications, earth science, remote sensing, and other major application areas.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1522505725
Category : Medical
Languages : en
Pages : 2118
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Book Description
Medical imaging has transformed the ways in which various conditions, injuries, and diseases are identified, monitored, and treated. As various types of digital visual representations continue to advance and improve, new opportunities for their use in medical practice will likewise evolve. Medical Imaging: Concepts, Methodologies, Tools, and Applications presents a compendium of research on digital imaging technologies in a variety of healthcare settings. This multi-volume work contains practical examples of implementation, emerging trends, case studies, and technological innovations essential for using imaging technologies for making medical decisions. This comprehensive publication is an essential resource for medical practitioners, digital imaging technologists, researchers, and medical students.
Author: Anbarasan, Kalaivani
Publisher: IGI Global
ISBN: 1799830934
Category : Medical
Languages : en
Pages : 248
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Book Description
Recent advancements in the technology of medical imaging, such as CT and MRI scanners, are making it possible to create more detailed 3D and 4D images. These powerful images require vast amounts of digital data to help with the diagnosis of the patient. Artificial intelligence (AI) must play a vital role in supporting with the analysis of this medical imaging data, but it will only be viable as long as healthcare professionals and AI interact to embrace deep thinking platforms such as automation in the identification of diseases in patients. AI Innovation in Medical Imaging Diagnostics is an essential reference source that examines AI applications in medical imaging that can transform hospitals to become more efficient in the management of patient treatment plans through the production of faster imaging and the reduction of radiation dosages through the PET and SPECT imaging modalities. The book also explores how data clusters from these images can be translated into small data packages that can be accessed by healthcare departments to give a real-time insight into patient care and required interventions. Featuring research on topics such as assistive healthcare, cancer detection, and machine learning, this book is ideally designed for healthcare administrators, radiologists, data analysts, computer science professionals, medical imaging specialists, diagnosticians, medical professionals, researchers, and students.
![Medical Image Storage Sysytem [sic] for Metadata-based Retrieval PDF](https://books.google.com/books/content/images/frontcover/MOFMMwEACAAJ?fife=w80-h100)
Author: Selwyn Onyebuchi Igwe
Publisher:
ISBN:
Category : Diagnostic imaging
Languages : en
Pages : 348
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Book Description
Large image databases have been used in various applications and in recent years. The major prerequisite of these databases is the means by which their contents can be indexed and retrieved. This dissertation presents an attempt to improve image storage using image data representation model that integrates both metadata and content-based image description in ORDBMS (Object Relational Database Management systems). This dissertation research is verified using real examples from the medical domain. Both image and salient objects are considered in this model. A prototype called MISS (Medical Image Storage System) has been realized to validate the key aspect of the approach used. This research work also presents initial work on the design and implementation of a prototype Medical Image Database System for the core medical image modalities. Based on a novel image data model and an original data repository model, this representation also supports salient object-relational data and adheres to the Digital Imaging and Communication in Medicine (DICOM) Standard. This standard, along with storage, metadata retrieval and processing of medical images are widely studied and researched in the domain of medical imaging. The efficiency of any image retrieval is strongly related to the representation of the model. The better the features of the image are represented in the metadata, the more efficient the image retrieval technique is able to satisfy complex queries. An object-relational database such as Oracle's multimedia formerly known as Oracle interMedia can provide a seamless integration of image data and metadata. A sample prototype application is presented in this research work. This representation can be applied to different application areas using the Object-Relational DBMS model. The Image databases are partitioned into similar images either by using a cluster generation technique, or by using external information about the content of the image. It is also important to state that the research study only focuses on efficient medical imaging storage and retrieval using metadata and not on content-based retrieval (CBR) using image processing techniques.
Author: Shiyuan Liu
Publisher: Springer Nature
ISBN: 9819984416
Category :
Languages : en
Pages : 448
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Book Description
Author: Stefan Matthias Florian Schmidt
Publisher:
ISBN: 9783980889612
Category :
Languages : en
Pages : 281
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Book Description
Author: Ayman El-Baz
Publisher: CRC Press
ISBN: 1351380737
Category : Computers
Languages : en
Pages : 330
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Book Description
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.
Author: R. Suganya
Publisher: CRC Press
ISBN: 1351366610
Category : Science
Languages : en
Pages : 145
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Book Description
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.
Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 0128131748
Category : Technology & Engineering
Languages : en
Pages : 292
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Book Description
Soft Computing Based Medical Image Analysis presents the foremost techniques of soft computing in medical image analysis and processing. It includes image enhancement, segmentation, classification-based soft computing, and their application in diagnostic imaging, as well as an extensive background for the development of intelligent systems based on soft computing used in medical image analysis and processing. The book introduces the theory and concepts of digital image analysis and processing based on soft computing with real-world medical imaging applications. Comparative studies for soft computing based medical imaging techniques and traditional approaches in medicine are addressed, providing flexible and sophisticated application-oriented solutions. Covers numerous soft computing approaches, including fuzzy logic, neural networks, evolutionary computing, rough sets and Swarm intelligence Presents transverse research in soft computing formation from various engineering and industrial sectors in the medical domain Highlights challenges and the future scope for soft computing based medical analysis and processing techniques
