Medical Image Databases
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Medical Image Databases
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Author : Stephen T.C. Wong
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Medical Image Databases written by Stephen T.C. Wong and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Medical categories.
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.
Big Data In Multimodal Medical Imaging
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Author : Ayman El-Baz
language : en
Publisher: CRC Press
Release Date : 2019-11-05
Big Data In Multimodal Medical Imaging written by Ayman El-Baz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-05 with Computers categories.
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.
Content Based Retrieval Of Medical Images
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Author : Paulo Mazzoncini de Azevedo-Marques
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2013-01-01
Content Based Retrieval Of Medical Images written by Paulo Mazzoncini de Azevedo-Marques and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-01 with Technology & Engineering categories.
Content-based image retrieval (CBIR) is the process of retrieval of images from a database that are similar to a query image, using measures derived from the images themselves, rather than relying on accompanying text or annotation. To achieve CBIR, the contents of the images need to be characterized by quantitative features; the features of the query image are compared with the features of each image in the database and images having high similarity with respect to the query image are retrieved and displayed. CBIR of medical images is a useful tool and could provide radiologists with assistance in the form of a display of relevant past cases. One of the challenging aspects of CBIR is to extract features from the images to represent their visual, diagnostic, or application-specific information content. In this book, methods are presented for preprocessing, segmentation, landmarking, feature extraction, and indexing of mammograms for CBIR. The preprocessing steps include anisotropic diffusion and the Wiener filter to remove noise and perform image enhancement. Techniques are described for segmentation of the breast and fibroglandular disk, including maximum entropy, a moment-preserving method, and Otsu's method. Image processing techniques are described for automatic detection of the nipple and the edge of the pectoral muscle via analysis in the Radon domain. By using the nipple and the pectoral muscle as landmarks, mammograms are divided into their internal, external, upper, and lower parts for further analysis. Methods are presented for feature extraction using texture analysis, shape analysis, granulometric analysis, moments, and statistical measures. The CBIR system presented provides options for retrieval using the Kohonen self-organizing map and the k-nearest-neighbor method. Methods are described for inclusion of expert knowledge to reduce the semantic gap in CBIR, including the query point movement method for relevance feedback (RFb). Analysis of performance is described in terms of precision, recall, and relevance-weighted precision of retrieval. Results of application to a clinical database of mammograms are presented, including the input of expert radiologists into the CBIR and RFb processes. Models are presented for integration of CBIR and computer-aided diagnosis (CAD) with a picture archival and communication system (PACS) for efficient workflow in a hospital. Table of Contents: Introduction to Content-based Image Retrieval / Mammography and CAD of Breast Cancer / Segmentation and Landmarking of Mammograms / Feature Extraction and Indexing of Mammograms / Content-based Retrieval of Mammograms / Integration of CBIR and CAD into Radiological Workflow
Image Databases
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Author : Vittorio Castelli
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-07
Image Databases written by Vittorio Castelli and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-07 with Computers categories.
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.
Deep Learning And Convolutional Neural Networks For Medical Imaging And Clinical Informatics
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Author : Le Lu
language : en
Publisher: Springer Nature
Release Date : 2019-09-19
Deep Learning And Convolutional Neural Networks For Medical Imaging And Clinical Informatics written by Le Lu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-19 with Computers categories.
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.
Feature Extraction In Medical Image Retrieval
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Author : Aswini Kumar Samantaray
language : en
Publisher: Springer
Release Date : 2024-05-15
Feature Extraction In Medical Image Retrieval written by Aswini Kumar Samantaray and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-15 with Computers categories.
Medical imaging is fundamental to modern healthcare, and its widespread use has resulted in creation of image databases. These repositories contain images from a diverse range of modalities, multidimensional as well as co-aligned multimodality images. These image collections offer opportunity for evidence-based diagnosis, teaching, and research. Advances in medical image analysis over last two decades shows there are now many algorithms and ideas available that allow to address medical image analysis tasks in commercial solutions with sufficient performance in terms of accuracy, reliability and speed. Content-based image retrieval (CBIR) is an image search technique that complements the conventional text-based retrieval of images by using visual features, such as color, texture, and shape, as search criteria. This book emphasizes the design of wavelet filter-banks as efficient and effective feature descriptors for medical image retrieval. Firstly, a generalized novel design of a family of multiplier-free orthogonal wavelet filter-banks is presented. In this, the dyadic filter coefficients are obtained based on double-shifting orthogonality property with allowable deviation from original filter coefficients. Next, a low complex symmetric Daub-4 orthogonal wavelet filter-bank is presented. This is achieved by slightly altering the perfect reconstruction condition to make designed filter-bank symmetric and to obtain dyadic filter coefficients. In third contribution, the first dyadic Gabor wavelet filter-bank is presented based on slight alteration in orientation parameter without disturbing remaining Gabor wavelet parameters. In addition, a novel feature descriptor based on the design of adaptive Gabor wavelet filter-bank is presented. The use of Maximum likelihood estimation is suggested to measure the similarity between the feature vectors of heterogeneous medical images. The performance of the suggested methods is evaluated on three different publicly available databases namely NEMA, OASIS and EXACT09. The performance in terms of average retrieval precision, average retrieval recall and computational time are compared with well-known existing methods.
Design And Prototype Of An Object Relational Database For Medical Imaged
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Author : Ngon Dong Dao
language : en
Publisher:
Release Date : 1998
Design And Prototype Of An Object Relational Database For Medical Imaged written by Ngon Dong Dao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
Advancement Of Machine Intelligence In Interactive Medical Image Analysis
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Author : Om Prakash Verma
language : en
Publisher: Springer Nature
Release Date : 2019-12-11
Advancement Of Machine Intelligence In Interactive Medical Image Analysis written by Om Prakash Verma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-11 with Computers categories.
The book discusses major technical advances and research findings in the field of machine intelligence in medical image analysis. It examines the latest technologies and that have been implemented in clinical practice, such as computational intelligence in computer-aided diagnosis, biological image analysis, and computer-aided surgery and therapy. This book provides insights into the basic science involved in processing, analysing, and utilising all aspects of advanced computational intelligence in medical decision-making based on medical imaging.
Soft Computing Based Medical Image Analysis
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2018-01-18
Soft Computing Based Medical Image Analysis written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-18 with Technology & Engineering categories.
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
Medical Imaging
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Author : Mostafa Analoui
language : en
Publisher: CRC Press
Release Date : 2012-11-08
Medical Imaging written by Mostafa Analoui and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-08 with Medical categories.
The discovery of x-ray, as a landmark event, enabled us to see the "invisible," opening a new era in medical diagnostics. More importantly, it offered a unique undestanding around the interaction of electromagnetic signal with human tissue and the utility of its selective absorption, scattering, diffusion, and reflection as a tool for understanding the physiology, evolution of disease, and therapy. With contributions from world-class experts, Medical Imaging: Principles and Practices offers a review of key imaging modalities with established clinical utilization and examples of quantitative tools for image analysis, modeling, and interpretation. The book provides a detailed overview of x-ray imaging and computed tomography, fundamental concepts in signal acquisition and processes, followed by an overview of functional MRI (fMRI) and chemical shift imaging. It also covers topics in Magnetic Resonance Microcopy, the physics of instrumentation and signal collection, and their application in clinical practice. Highlights include a chapter offering a unique perspective on the use of quantitative PET for its applications in drug discovery and development, which is rapidly becoming an indispensible tool for clinical and research applications, and a chapter addressing the key issues around organizing and searching multimodality data sets, an increasingly important yet challenging issue in clinical imaging. Topics include: X-ray imaging and computed tomography MRI and magnetic resonance microscopy Nuclear imaging Ultrasound imaging Electrical Impedance Tomography (EIT) Emerging technologies for in vivo imaging Contrast-enhanced MRI MR approaches for osteoarthritis and cardiovascular imaging PET quantitative imaging for drug development Medical imaging data mining and search The selection of topics provides readers with an appreciation of the depth and breadth of the field and the challenges ahead of the technical and clinical community ofresearchers and practitioners.