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 nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis

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  • Author : Tapan K. Gandhi
  • Publisher : Academic Press
  • Pages : 308 pages
  • ISBN : 0128192968
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKAdvanced Machine Vision Paradigms for Medical Image Analysis

Advanced Machine Vision Paradigms for Medical Image Analysis

Advanced Machine Vision Paradigms for Medical Image Analysis
  • Author : Tapan K. Gandhi,Siddhartha Bhattacharyya,Sourav De,Debanjan Konar,Sandip Dey
  • Publisher : Academic Press
  • Release : 11 August 2020
GET THIS BOOKAdvanced 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

Deep Learning for Medical Image Analysis

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  • Publisher : Academic Press
  • Release : 18 January 2017
GET THIS BOOKDeep Learning for Medical Image Analysis

Deep learning is providing exciting solutions for medical image analysis problems and is seen as 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 have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great

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  • Publisher : Springer Nature
  • Release : 28 August 2019
GET THIS BOOKComputer Vision and Machine Intelligence in Medical Image Analysis

This book includes high-quality papers presented at the Symposium 2019, organised by Sikkim Manipal Institute of Technology (SMIT), in Sikkim from 26–27 February 2019. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.

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  • Publisher : Springer Nature
  • Release : 07 December 2019
GET THIS BOOKComputer Vision in Advanced Control Systems-5

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  • Author : Anke Meyer-Baese,Volker J. Schmid
  • Publisher : Elsevier
  • Release : 21 March 2014
GET THIS BOOKPattern Recognition and Signal Analysis in Medical Imaging

Medical imaging is one of the heaviest funded biomedical engineering research areas. The second edition of Pattern Recognition and Signal Analysis in Medical Imaging brings sharp focus to the development of integrated systems for use in the clinical sector, enabling both imaging and the automatic assessment of the resultant data. Since the first edition, there has been tremendous development of new, powerful technologies for detecting, storing, transmitting, analyzing, and displaying medical images. Computer-aided analytical techniques, coupled with a continuing need

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  • Publisher : Springer
  • Release : 13 October 2017
GET THIS BOOKAdvances 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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  • Publisher : Academic Press
  • Release : 05 March 2020
GET THIS BOOKHybrid Computational Intelligence

Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of

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  • Author : Xavier Pennec,Stefan Sommer,Tom Fletcher
  • Publisher : Academic Press
  • Release : 02 September 2019
GET THIS BOOKRiemannian Geometric Statistics in Medical Image Analysis

Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a

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  • Publisher : Academic Press
  • Release : 29 June 2019
GET THIS BOOKComputational Retinal Image Analysis

Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference

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  • Publisher : Academic Press
  • Release : 11 December 2015
GET THIS BOOKMedical Image Recognition, Segmentation and Parsing

This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods,

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  • Publisher : CRC Press
  • Release : 25 November 2019
GET THIS BOOKArtificial Intelligence in Medical Imaging

This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed

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  • Publisher : Springer
  • Release : 07 June 2014
GET THIS BOOKNatural User Interfaces in Medical Image Analysis

This unique text/reference highlights a selection of practical applications of advanced image analysis methods for medical images. The book covers the complete methodology for processing, analysing and interpreting diagnostic results of sample CT images. The text also presents significant problems related to new approaches and paradigms in image understanding and semantic image analysis. To further engage the reader, example source code is provided for the implemented algorithms in the described solutions. Features: describes the most important methods and algorithms

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  • Author : Gonzalez, Fabio A.,Romero, Eduardo
  • Publisher : IGI Global
  • Release : 31 December 2009
GET THIS BOOKBiomedical Image Analysis and Machine Learning Technologies: Applications and Techniques

Medical images are at the base of many routine clinical decisions and their influence continues to increase in many fields of medicine. Since the last decade, computers have become an invaluable tool for supporting medical image acquisition, processing, organization and analysis. Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques provides a panorama of the current boundary between biomedical complexity coming from the medical image context and the multiple techniques which have been used for solving many of these

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  • Publisher : Springer Science & Business Media
  • Release : 03 January 2008
GET THIS BOOKModern Computational Intelligence Methods for the Interpretation of Medical Images

This work by two accomplished Polish researchers provides medical technicians and researchers alike with detailed descriptions of up-to-date methods used for computer processing and interpretation of medical images. The broad scope of the book takes in images acquisition, storing with compression, processing, analysis, recognition and also its automatic understanding. The introduction provides a general overview of the computer vision methods designed for medical images.

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  • Release : 29 November 2010
GET THIS BOOKAlgorithms for Image Processing and Computer Vision

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