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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
Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 0128131748
Category : Technology & Engineering
Languages : en
Pages : 292
Get Book Here
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
Author: Yanhui Guo
Publisher: Academic Press
ISBN: 0128181494
Category : Computers
Languages : en
Pages : 372
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Book Description
Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set's novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis. - Introduces the mathematical model and concepts of neutrosophic theory and methods - Highlights the different techniques of neutrosophic theory, focusing on applying the neutrosophic set in image analysis to support computer- aided diagnosis (CAD) systems, including approaches from soft computing and machine learning - Shows how NS techniques can be applied to medical image denoising, segmentation and classification - Provides challenges and future directions in neutrosophic set based medical image analysis
Author: G.R. SINHA
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8120349024
Category : Technology & Engineering
Languages : en
Pages : 270
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Book Description
Medical Image Processing: Concepts and Applications presents an overview of image processing for various applications in the field of medical science. Inclusion of several topics like noise reduction filters, feature extraction, image restoration, segmentation, soft computing techniques and context-based medical image retrieval, etc. makes this book a single-source information meeting the requirements of the readers. Besides, the coverage of digital image processing, human visual perception and CAD system to be used in automated diagnosis system, medical imaging modalities, various application areas of medical field, detection and classification of various disease, etc. is highly emphasised in the book. The book, divided into eight chapters, presents the topics in a clear, simple, practical and cogent fashion that provides the students with the insight into theory as well as applications to the practical problems. The research orientation of the book greatly supports the concepts of image processing to be applied for segmentation, classification and detection of affected areas in X-ray, MRI and mammographic and all other medical images. Throughout the book, an attempt has been made to address the challenges faced by radiologists, physicians and doctors in scanning, interpretation and diagnosis process. The book uses an abundance of colour images to impart a high level of comprehension of concepts and helps in mastering the process of medical image processing. Special attention is made on the review of algorithms or methods of medical image formation, processing and analysis, medical imaging applications, and emerging medical imaging modality. This is purely a text dedicated for the undergraduate and postgraduate students of biomedical engineering. The book is also of immense use to the students of computer science engineering and IT who offer a course on digital image processing. Key Points • Chapter-end review questions test the students’ knowledge of the funda-mental concepts. • Course outcomes help the students in capturing the key points. • Several images and information regarding morphological operations given in appendices help in getting additional knowledge in the field of medical image processing.
Author: Yaochu Jin
Publisher: Springer Science & Business Media
ISBN: 3540899677
Category : Computers
Languages : en
Pages : 336
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Book Description
Biological systems are inherently stochastic and uncertain. Thus, research in bioinformatics, biomedical engineering and computational biology has to deal with a large amount of uncertainties. Fuzzy logic has shown to be a powerful tool in capturing different uncertainties in engineering systems. In recent years, fuzzy logic based modeling and analysis approaches are also becoming popular in analyzing biological data and modeling biological systems. Numerous research and application results have been reported that demonstrated the effectiveness of fuzzy logic in solving a wide range of biological problems found in bioinformatics, biomedical engineering, and computational biology. Contributed by leading experts world-wide, this edited book contains 16 chapters presenting representative research results on the application of fuzzy systems to genome sequence assembly, gene expression analysis, promoter analysis, cis-regulation logic analysis and synthesis, reconstruction of genetic and cellular networks, as well as biomedical problems, such as medical image processing, electrocardiogram data classification and anesthesia monitoring and control. This volume is a valuable reference for researchers, practitioners, as well as graduate students working in the field of bioinformatics, biomedical engineering and computational biology.
Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 012816087X
Category : Science
Languages : en
Pages : 348
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Book Description
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. - Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging - Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining - Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains
Author: Dey, Nilanjan
Publisher: IGI Global
ISBN: 1522563172
Category : Medical
Languages : en
Pages : 360
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Book Description
Medical imaging technologies play a significant role in visualization and interpretation methods in medical diagnosis and practice using decision making, pattern classification, diagnosis, and learning. Progressions in the field of medical imaging lead to interdisciplinary discovery in microscopic image processing and computer-assisted diagnosis systems, and aids physicians in the diagnosis and early detection of diseases. Histopathological Image Analysis in Medical Decision Making provides emerging research exploring the theoretical and practical applications of image technologies and feature extraction procedures within the medical field. Featuring coverage on a broad range of topics such as image classification, digital image analysis, and prediction methods, this book is ideally designed for medical professionals, system engineers, medical students, researchers, and medical practitioners seeking current research on problem-oriented processing techniques in imaging technologies.
Author: Patricia Melin
Publisher: Springer Science & Business Media
ISBN: 3642151108
Category : Computers
Languages : en
Pages : 449
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Book Description
This book describes bio-inspired models and applications of hybrid intelligent systems using soft computing techniques for image analysis and pattern recognition based on biometrics and other sources. Each section groups papers on a similar subject.
Author: S. Kevin Zhou
Publisher: Academic Press
ISBN: 0323858880
Category : Computers
Languages : en
Pages : 544
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Book Description
Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis.· Covers common research problems in medical image analysis and their challenges · Describes the latest deep learning methods and the theories behind approaches for medical image analysis · Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment · Includes a Foreword written by Nicholas Ayache
Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 0128180056
Category : Science
Languages : en
Pages : 220
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Book Description
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
Author: Aboul Ella Hassanien
Publisher: CRC Press
ISBN: 1351030361
Category : Computers
Languages : en
Pages : 350
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Book Description
Big data and the Internet of Things (IoT) play a vital role in prediction systems used in biological and medical applications, particularly for resolving issues related to disease biology at different scales. Modelling and integrating medical big data with the IoT helps in building effective prediction systems for automatic recommendations of diagnosis and treatment. The ability to mine, process, analyse, characterize, classify and cluster a variety and wide volume of medical data is a challenging task. There is a great demand for the design and development of methods dealing with capturing and automatically analysing medical data from imaging systems and IoT sensors. Addressing analytical and legal issues, and research on integration of big data analytics with respect to clinical practice and clinical utility, architectures and clustering techniques for IoT data processing, effective frameworks for removal of misclassified instances, practicality of big data analytics, methodological and technical issues, potential of Hadoop in managing healthcare data is the need of the hour. This book integrates different aspects used in the field of healthcare such as big data, IoT, soft computing, machine learning, augmented reality, organs on chip, personalized drugs, implantable electronics, integration of bio-interfaces, and wearable sensors, devices, practical body area network (BAN) and architectures of web systems. Key Features: Addresses various applications of Medical Big Data and Internet of Medical Things in real time environment Highlights recent innovations, designs, developments and topics of interest in machine learning techniques for classification of medical data Provides background and solutions to existing challenges in Medical Big Data and Internet of Medical Things Provides optimization techniques and programming models to parallelize the computationally intensive tasks in data mining of medical data Discusses interactions, advantages, limitations, challenges and future perspectives of IoT based remote healthcare monitoring systems. Includes data privacy and security analysis of cryptography methods for the Web of Medical Things (WoMT) Presents case studies on the next generation medical chair, electronic nose and pill cam are also presented.
