Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images.
Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges
Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications
Introduces several techniques for medical image processing and analysis for CAD systems design
Автор: Jacob Scharcanski; M. Emre Celebi Название: Computer Vision Techniques for the Diagnosis of Skin Cancer ISBN: 3642396070 ISBN-13(EAN): 9783642396076 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Although computerized techniques cannot as yet provide a definitive diagnosis, they can be used to improve biopsy decision-making as well as early melanoma detection, especially for patients with multiple atypical nevi.
Описание: This book covers virtually all aspects of image formation in medical imaging, including systems based on ionizing radiation (x-rays, gamma rays) and non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike.
Описание: Computer-aided design (CAD) plays a key role in improving biomedical systems for various applications. It also helps in the detection, identification, predication, analysis, and classification of diseases, in the management of chronic conditions, and in the delivery of health services. This book discusses the uses of CAD to solve real-world problems and challenges in biomedical systems with the help of appropriate case studies and research simulation results. Aiming to overcome the gap between CAD and biomedical science, it describes behaviors, concepts, fundamentals, principles, case studies, and future directions for research, including the automatic identification of related disorders using CAD. Features:Proposes CAD for the study of biomedical signals to understand physiology and to improve healthcare systems’ ability to diagnose and identify health disorders. Presents concepts of CAD for biomedical modalities in different disorders. Discusses design and simulation examples, issues, and challenges. Illustrates bio-potential signals and their appropriate use in studying different disorders. Includes case studies, practical examples, and research directions. Computer-Aided Design and Diagnosis Methods for Biometrical Applications is aimed at researchers, graduate students in biomedical engineering, image processing, biomedical technology, medical imaging, and health informatics.
An introduction to the computer-based modeling of influenza, a continuing major worldwide communicable disease.
The use of (1) as an illustration of a methodology for the computer-based modeling of communicable diseases.
For the purposes of (1) and (2), a basic influenza model is formulated as a system of partial differential equations (PDEs) that define the spatiotemporal evolution of four populations: susceptibles, untreated and treated infecteds, and recovereds. The requirements of a well-posed PDE model are considered, including the initial and boundary conditions. The terms of the PDEs are explained.
The computer implementation of the model is illustrated with a detailed line-by-line explanation of a system of routines in R (a quality, open-source scientific computing system that is readily available from the Internet). The R routines demonstrate the straightforward numerical solution of a system of nonlinear PDEs by the method of lines (MOL), an established general algorithm for PDEs.
The presentation of the PDE modeling methodology is introductory with a minumum of formal mathematics (no theorems and proofs), and with emphasis on example applications. The intent of the book is to assist in the initial understanding and use of PDE mathematical modeling of communicable diseases, and the explanation and interpretation of the computed model solutions, as illustrated with the influenza model.
An introduction to the computer-based modeling of influenza, a continuing major worldwide communicable disease.
The use of (1) as an illustration of a methodology for the computer-based modeling of communicable diseases.
For the purposes of (1) and (2), a basic influenza model is formulated as a system of partial differential equations (PDEs) that define the spatiotemporal evolution of four populations: susceptibles, untreated and treated infecteds, and recovereds. The requirements of a well-posed PDE model are considered, including the initial and boundary conditions. The terms of the PDEs are explained.
The computer implementation of the model is illustrated with a detailed line-by-line explanation of a system of routines in R (a quality, open-source scientific computing system that is readily available from the Internet). The R routines demonstrate the straightforward numerical solution of a system of nonlinear PDEs by the method of lines (MOL), an established general algorithm for PDEs.
The presentation of the PDE modeling methodology is introductory with a minumum of formal mathematics (no theorems and proofs), and with emphasis on example applications. The intent of the book is to assist in the initial understanding and use of PDE mathematical modeling of communicable diseases, and the explanation and interpretation of the computed model solutions, as illustrated with the influenza model.
Автор: Jacob Scharcanski; M. Emre Celebi Название: Computer Vision Techniques for the Diagnosis of Skin Cancer ISBN: 3662522624 ISBN-13(EAN): 9783662522622 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Although computerized techniques cannot as yet provide a definitive diagnosis, they can be used to improve biopsy decision-making as well as early melanoma detection, especially for patients with multiple atypical nevi.
Автор: Xiao-Xia Yin; Sillas Hadjiloucas; Yanchun Zhang Название: Pattern Classification of Medical Images: Computer Aided Diagnosis ISBN: 3319570269 ISBN-13(EAN): 9783319570266 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis.
Описание: 1. Fixed Boundary PDE Model Formulation2. Fixed Boundary PDE Model Implementation3. Fixed Boundary PDE Model Output4. Moving Boundary PDE Model Implementation5. Moving Boundary PDE Model OutputIndex
Автор: Yin Xiao-Xia, Hadjiloucas Sillas, Zhang Yanchun Название: Pattern Classification of Medical Images: Computer Aided Diagnosis ISBN: 3319860615 ISBN-13(EAN): 9783319860619 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis.
Описание: An Introduction to Breast Cancer Diagnosis, Prognosis, and Artificial Intelligence.- Breast Cancer and Its Types.- Artificial Intelligence.- Breast Cancer Screening Using AI Methods.- Case Study for Screening of Breast Cancer.
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