Medical Image Databases

Medical Image Databases
Author: Stephen T.C. Wong
Publisher: Springer Science & Business Media
Total Pages: 405
Release: 2012-12-06
Genre: Medical
ISBN: 1461555531
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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.

Image Databases

Image Databases
Author: Vittorio Castelli
Publisher: John Wiley & Sons
Total Pages: 609
Release: 2004-04-07
Genre: Computers
ISBN: 0471464074
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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.

AI Innovation in Medical Imaging Diagnostics

AI Innovation in Medical Imaging Diagnostics
Author: Kalaivani Anbarasan
Publisher: Medical Information Science Reference
Total Pages: 300
Release: 2020
Genre:
ISBN: 9781799830924
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"This book examines the application of artificial intelligence in medical imaging diagnostics"--

Medical Image Storage Sysytem [sic] for Metadata-based Retrieval

Medical Image Storage Sysytem [sic] for Metadata-based Retrieval
Author: Selwyn Onyebuchi Igwe
Publisher:
Total Pages: 348
Release: 2011
Genre: Diagnostic imaging
ISBN:
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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.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Erik R. Ranschaert
Publisher: Springer
Total Pages: 373
Release: 2019-01-29
Genre: Medical
ISBN: 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.

Big Data in Medical Image Processing

Big Data in Medical Image Processing
Author: R. Suganya
Publisher: CRC Press
Total Pages: 145
Release: 2018-01-29
Genre: Science
ISBN: 1351366610
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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.

Medical Imaging: Concepts, Methodologies, Tools, and Applications

Medical Imaging: Concepts, Methodologies, Tools, and Applications
Author: Management Association, Information Resources
Publisher: IGI Global
Total Pages: 2118
Release: 2016-07-18
Genre: Medical
ISBN: 1522505725
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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.

Soft Computing Based Medical Image Analysis

Soft Computing Based Medical Image Analysis
Author: Nilanjan Dey
Publisher: Academic Press
Total Pages: 292
Release: 2018-01-18
Genre: Technology & Engineering
ISBN: 0128131748
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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