Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

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  • Author : Nilanjan Dey
  • Publisher : Academic Press
  • Pages : 218 pages
  • ISBN : 0128180056
  • Rating : /5 from reviews
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Download or Read online Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis full in PDF, ePub and kindle. this book written by Nilanjan Dey and published by Academic Press which was released on 31 July 2019 with total page 218 pages. We cannot guarantee that Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis
  • Author : Nilanjan Dey
  • Publisher : Academic Press
  • Release : 31 July 2019
GET THIS BOOK Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

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

Pattern Classification of Medical Images Computer Aided Diagnosis

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  • Publisher : Springer
  • Release : 27 June 2017
GET THIS BOOK Pattern Classification of Medical Images Computer Aided Diagnosis

This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis. The analysis of time-series images is one of the most widely appearing problems in science, engineering, and business. In recent years this problem has gained importance due to the increasing availability of more sensitive sensors in science and engineering and due to the wide-spread use of computers in corporations which have increased the amount of time-series data collected by

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  • Release : 23 November 2017
GET THIS BOOK Medical Image Analysis and Informatics

With the development of rapidly increasing medical imaging modalities and their applications, the need for computers and computing in image generation, processing, visualization, archival, transmission, modeling, and analysis has grown substantially. Computers are being integrated into almost every medical imaging system. Medical Image Analysis and Informatics demonstrates how quantitative analysis becomes possible by the application of computational procedures to medical images. Furthermore, it shows how quantitative and objective analysis facilitated by medical image informatics, CBIR, and CAD could lead to

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  • Publisher : Springer Nature
  • Release : 06 February 2020
GET THIS BOOK Deep Learning in Medical Image Analysis

This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical

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GET THIS BOOK Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing techniques and enormous advancements in the field. The book focuses on the cross-disciplinary mechanisms and ground-breaking research ideas on novel techniques and data processing approaches in handling structured and unstructured healthcare data. It also gives insight into various information-processing models and many memories associated with it while processing the information for forecasting future trends and decision

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GET THIS BOOK Intelligent Vision in Healthcare

This book focuses on various aspects of computer vision applications in the field of healthcare. It covers new tools and technologies in some of the important areas of medical science like histopathological image analysis, cancer taxonomy, use of deep learning architecture dental care, and many more. Furthermore, this book reviews and discusses the use of intelligent learning-based algorithms for increasing the precision in medical domain. The book discusses different computer vision algorithms which are useful in various industries and day-to-day

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GET THIS BOOK Machine Learning and IoT for Intelligent Systems and Smart Applications

The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described

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GET THIS BOOK Advances in Data Science and Intelligent Data Communication Technologies for COVID 19

This book presents the emerging developments in intelligent computing, machine learning, and data mining. It also provides insights on communications, network technologies, and the Internet of things. It offers various insights on the role of the Internet of things against COVID-19 and its potential applications. It provides the latest cloud computing improvements and advanced computing and addresses data security and privacy to secure COVID-19 data.

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GET THIS BOOK Breast Imaging

Early detection of breast cancer with screening mammography is still the best method we have in saving countless women's lives and decreasing the harms of overtreatment. This textbook encompasses relevant topics in daily patient care with breast imaging to technical innovations for improving breast cancer detection and treatment.

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  • Publisher : Academic Press
  • Release : 11 August 2020
GET THIS BOOK Advanced Machine Vision Paradigms for Medical Image Analysis

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured

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  • Publisher : Springer
  • Release : 13 October 2017
GET THIS BOOK Advances in Soft Computing and Machine Learning in Image Processing

This book is a collection of the latest applications of methods from soft computing and machine learning in image processing. It explores different areas ranging from image segmentation to the object recognition using complex approaches, and includes the theory of the methodologies used to provide an overview of the application of these tools in image processing. The material has been compiled from a scientific perspective, and the book is primarily intended for undergraduate and postgraduate science, engineering, and computational mathematics

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  • Release : 02 July 2020
GET THIS BOOK Medical Imaging and Computer Aided Diagnosis

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  • Release : 10 November 2017
GET THIS BOOK Classification in BioApps

This book on classification in biomedical image applications presents original and valuable research work on advances in this field, which covers the taxonomy of both supervised and unsupervised models, standards, algorithms, applications and challenges. Further, the book highlights recent scientific research on artificial neural networks in biomedical applications, addressing the fundamentals of artificial neural networks, support vector machines and other advanced classifiers, as well as their design and optimization. In addition to exploring recent endeavours in the multidisciplinary domain of

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GET THIS BOOK Machine Learning and Deep Learning Techniques for Medical Science

The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing

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  • Release : 01 January 2019
GET THIS BOOK Computer Aided Intervention and Diagnostics in Clinical and Medical Images

This book is a compendium of the ICCMIA 2018 proceedings, which provides an ideal reference for all medical imaging researchers and professionals to explore innovative methods and analyses on imaging technologies for better prospective patient care. This work serves as an exclusive source for new computer assisted clinical and medical developments in imaging diagnosis, intervention and analysis. It includes articles on computer assisted medical scanning techniques, computer-aided diagnosis, robotic surgery and imaging, imaging genomics, clinically-oriented imaging physics and informatics, augmented-reality medical