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Advanced Machine Vision Paradigms for Medical Image Analysis

Advanced Machine Vision Paradigms for Medical Image Analysis
A Book

by Tapan K. Gandhi,Siddhartha Bhattacharyya,Sourav De,Debanjan Konar,Sandip Dey

  • Publisher : Academic Press
  • Release : 2020-08-11
  • Pages : 308
  • ISBN : 0128192968
  • Language : En, Es, Fr & De
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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

Deep Learning for Medical Image Analysis

Deep Learning for Medical Image Analysis
A Book

by S. Kevin Zhou,Hayit Greenspan,Dinggang Shen

  • Publisher : Academic Press
  • Release : 2017-01-18
  • Pages : 458
  • ISBN : 0128104090
  • Language : En, Es, Fr & De
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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 learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes 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 Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

Soft Computing Based Medical Image Analysis

Soft Computing Based Medical Image Analysis
A Book

by Nilanjan Dey,Amira Ashour,Fuquian Shi,Valentina E. Balas

  • Publisher : Academic Press
  • Release : 2018-01-18
  • Pages : 292
  • ISBN : 0128131748
  • Language : En, Es, Fr & De
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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

Computer Vision and Machine Intelligence in Medical Image Analysis

Computer Vision and Machine Intelligence in Medical Image Analysis
International Symposium, ISCMM 2019

by Mousumi Gupta,Debanjan Konar,Siddhartha Bhattacharyya,Sambhunath Biswas

  • Publisher : Springer Nature
  • Release : 2019-08-28
  • Pages : 150
  • ISBN : 9811387982
  • Language : En, Es, Fr & De
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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.

Hybrid Machine Intelligence for Medical Image Analysis

Hybrid Machine Intelligence for Medical Image Analysis
A Book

by Siddhartha Bhattacharyya,Debanjan Konar,Jan Platos,Chinmoy Kar,Kalpana Sharma

  • Publisher : Springer
  • Release : 2019-08-08
  • Pages : 293
  • ISBN : 9811389306
  • Language : En, Es, Fr & De
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The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.

Advanced Computational Intelligence Paradigms in Healthcare - 3

Advanced Computational Intelligence Paradigms in Healthcare - 3
A Book

by Margarita Sordo,Sachin Vaidya

  • Publisher : Springer
  • Release : 2008-08-20
  • Pages : 257
  • ISBN : 3540776621
  • Language : En, Es, Fr & De
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This volume details the latest state-of-the-art research on computational intelligence paradigms in healthcare in the intelligent agent environment. The book presents seven chapters selected from the rapidly growing application areas of computational intelligence to healthcare systems. These include intelligent synthetic characters, man-machine interface, menu generators, analysis of user acceptance, pictures archiving and communication systems.

Computer Vision in Advanced Control Systems-5

Computer Vision in Advanced Control Systems-5
Advanced Decisions in Technical and Medical Applications

by Margarita N. Favorskaya,Lakhmi C. Jain

  • Publisher : Springer Nature
  • Release : 2019-12-07
  • Pages : 321
  • ISBN : 3030337952
  • Language : En, Es, Fr & De
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This book applies novel theories to improve algorithms in complex data analysis in various fields, including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. It is intended for Ph.D. students, academics, researchers, and software developers working in the areas of digital video processing and computer vision technologies.

Riemannian Geometric Statistics in Medical Image Analysis

Riemannian Geometric Statistics in Medical Image Analysis
A Book

by Xavier Pennec,Stefan Sommer,Tom Fletcher

  • Publisher : Academic Press
  • Release : 2019-09-02
  • Pages : 636
  • ISBN : 0128147261
  • Language : En, Es, Fr & De
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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 presentation of state-of-the-art methods. Beyond medical image computing, the methods described in this book may also apply to other domains such as signal processing, computer vision, geometric deep learning, and other domains where statistics on geometric features appear. As such, the presented core methodology takes its place in the field of geometric statistics, the statistical analysis of data being elements of nonlinear geometric spaces. The foundational material and the advanced techniques presented in the later parts of the book can be useful in domains outside medical imaging and present important applications of geometric statistics methodology Content includes: The foundations of Riemannian geometric methods for statistics on manifolds with emphasis on concepts rather than on proofs Applications of statistics on manifolds and shape spaces in medical image computing Diffeomorphic deformations and their applications As the methods described apply to domains such as signal processing (radar signal processing and brain computer interaction), computer vision (object and face recognition), and other domains where statistics of geometric features appear, this book is suitable for researchers and graduate students in medical imaging, engineering and computer science. A complete reference covering both the foundations and state-of-the-art methods Edited and authored by leading researchers in the field Contains theory, examples, applications, and algorithms Gives an overview of current research challenges and future applications

Pattern Recognition and Signal Analysis in Medical Imaging

Pattern Recognition and Signal Analysis in Medical Imaging
A Book

by Anke Meyer-Baese,Volker J. Schmid

  • Publisher : Elsevier
  • Release : 2014-03-21
  • Pages : 466
  • ISBN : 0124166156
  • Language : En, Es, Fr & De
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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 to derive more information from medical images, has led to a growing application of digital processing techniques in cancer detection as well as elsewhere in medicine. This book is an essential tool for students and professionals, compiling and explaining proven and cutting-edge methods in pattern recognition for medical imaging. New edition has been expanded to cover signal analysis, which was only superficially covered in the first edition New chapters cover Cluster Validity Techniques, Computer-Aided Diagnosis Systems in Breast MRI, Spatio-Temporal Models in Functional, Contrast-Enhanced and Perfusion Cardiovascular MRI Gives readers an unparalleled insight into the latest pattern recognition and signal analysis technologies, modeling, and applications

Medical Image Recognition, Segmentation and Parsing

Medical Image Recognition, Segmentation and Parsing
Machine Learning and Multiple Object Approaches

by S. Kevin Zhou

  • Publisher : Academic Press
  • Release : 2015-12-11
  • Pages : 542
  • ISBN : 0128026766
  • Language : En, Es, Fr & De
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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, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects Methods and theories for medical image recognition, segmentation and parsing of multiple objects Efficient and effective machine learning solutions based on big datasets Selected applications of medical image parsing using proven algorithms Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets Includes algorithms for recognizing and parsing of known anatomies for practical applications

Computer Analysis of Images and Patterns

Computer Analysis of Images and Patterns
15th International Conference, CAIP 2013, York, UK, August 27-29, 2013, Proceedings

by Richard Wilson,Edwin Hancock,Adrian Bors,William Smith

  • Publisher : Springer
  • Release : 2013-08-17
  • Pages : 583
  • ISBN : 3642402461
  • Language : En, Es, Fr & De
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The two volume set LNCS 8047 and 8048 constitutes the refereed proceedings of the 15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013, held in York, UK, in August 2013. The 142 papers presented were carefully reviewed and selected from 243 submissions. The scope of the conference spans the following areas: 3D TV, biometrics, color and texture, document analysis, graph-based methods, image and video indexing and database retrieval, image and video processing, image-based modeling, kernel methods, medical imaging, mobile multimedia, model-based vision approaches, motion analysis, natural computation for digital imagery, segmentation and grouping, and shape representation and analysis.

Advances in Soft Computing and Machine Learning in Image Processing

Advances in Soft Computing and Machine Learning in Image Processing
A Book

by Aboul Ella Hassanien,Diego Alberto Oliva

  • Publisher : Springer
  • Release : 2017-10-13
  • Pages : 718
  • ISBN : 3319637541
  • Language : En, Es, Fr & De
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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 students. It can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence, and is a valuable resource for researchers in the evolutionary computation, artificial intelligence and image processing communities.

Natural User Interfaces in Medical Image Analysis

Natural User Interfaces in Medical Image Analysis
Cognitive Analysis of Brain and Carotid Artery Images

by Marek R. Ogiela,Tomasz Hachaj

  • Publisher : Springer
  • Release : 2014-06-07
  • Pages : 288
  • ISBN : 3319078003
  • Language : En, Es, Fr & De
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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 used for image analysis; examines the fundamentals of cognitive computer image analysis for computer-aided diagnosis and semantic image description; presents original approaches for the semantic analysis of CT perfusion and CT angiography images of the brain and carotid artery; discusses techniques for creating 3D visualisations of large datasets; reviews natural user interfaces in medical imaging systems, including GDL technology.

Computational Retinal Image Analysis

Computational Retinal Image Analysis
Tools, Applications and Perspectives

by Emanuele Trucco,Tom MacGillivray,Yanwu Xu

  • Publisher : Academic Press
  • Release : 2019-11-25
  • Pages : 502
  • ISBN : 0081028172
  • Language : En, Es, Fr & De
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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 is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. Provides a unique, well-structured and integrated overview of retinal image analysis Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care Includes plans and aspirations of companies and professional bodies

Advanced Computational Intelligence in Healthcare-7

Advanced Computational Intelligence in Healthcare-7
Biomedical Informatics

by Ilias Maglogiannis,Sheryl Brahnam,Lakhmi C. Jain

  • Publisher : Springer Nature
  • Release : 2020-03-23
  • Pages : 161
  • ISBN : 3662611147
  • Language : En, Es, Fr & De
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This book presents state-of-the-art works and systematic reviews in the emerging field of computational intelligence (CI) in electronic health care. The respective chapters present surveys and practical examples of artificial intelligence applications in the areas of Human-Machine Interface (HMI) and affective computing, machine learning, big health data and visualization analytics, computer vision and medical image analysis. The book also addresses new and emerging topics in CI for health care such as the utilization of Social Media (SM) and the introduction of new intelligent paradigms in the security and privacy domains, which are critical for the health sector. The chapters, while of course not exhaustively addressing all the possible aspects of the aforementioned areas, are indicative of the dynamic nature of interdisciplinary research being pursued. Accordingly, the book is intended not only for researchers in the respective fields, but also for medical and administrative personnel working in the health sector, as well as managers and stakeholders responsible for making strategic decisions and defining public health policies.

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications
A Book

by Exarchos, Themis P.,Papadopoulos, Athanasios,Fotiadis, Dimitrios I.

  • Publisher : IGI Global
  • Release : 2009-04-30
  • Pages : 598
  • ISBN : 1605663158
  • Language : En, Es, Fr & De
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"This book includes state-of-the-art methodologies that introduce biomedical imaging in decision support systems and their applications in clinical practice"--Provided by publisher.

Algorithms for Image Processing and Computer Vision

Algorithms for Image Processing and Computer Vision
A Book

by J. R. Parker

  • Publisher : John Wiley & Sons
  • Release : 2010-11-29
  • Pages : 504
  • ISBN : 9781118021880
  • Language : En, Es, Fr & De
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A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists who require highly specialized image processing. Algorithms now exist for a wide variety of sophisticated image processing applications required by software engineers and developers, advanced programmers, graphics programmers, scientists, and related specialists This bestselling book has been completely updated to include the latest algorithms, including 2D vision methods in content-based searches, details on modern classifier methods, and graphics cards used as image processing computational aids Saves hours of mathematical calculating by using distributed processing and GPU programming, and gives non-mathematicians the shortcuts needed to program relatively sophisticated applications. Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.

Computational Intelligence Paradigms in Advanced Pattern Classification

Computational Intelligence Paradigms in Advanced Pattern Classification
A Book

by Marek R. Ogiela,Lakhmi C Jain

  • Publisher : Springer
  • Release : 2012-01-13
  • Pages : 199
  • ISBN : 3642240496
  • Language : En, Es, Fr & De
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This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of cognitive systems for image computer understanding, moving object detection, advanced image filtration and intelligent multi-object labelling and classification. It is directed to the scientists, application engineers, professors, professors and students will find this book useful.

Advances in Image Processing and Understanding

Advances in Image Processing and Understanding
A Festschrift for Thomas S. Huang

by Alan Conrad Bovik,Chang Wen Chen,Dmitry B. Goldgof

  • Publisher : World Scientific
  • Release : 2002
  • Pages : 390
  • ISBN : 9812380914
  • Language : En, Es, Fr & De
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This volume of original papers has been assembled to honor the achievements of Professor Thomas S Huang in the area of image processing and image analysis. Professor Huang's life of inquiry has spanned a number of decades as his work on imaging problems began in 1960's. Over these 40 years, he has made many fundamental and pioneering contributions to nearly every area of this field. Professor Huang has received numerous Awards, including the prestigious Jack Kilby Signal Processing Medal from IEEE. He has been elected to the National Academy of Engineering, and named Fellow of IEEE, Fellow of OSA, Fellow of IAPR, and Fellow of SPIE. Professor Huang has made fundamental contributions to image processing, pattern recognition, and computer vision: including design and stability test of multidimensional digital filters, digital holography; compression techniques for documents and images; 3D motion and modeling, analysis and visualization of the human face, hand and body, multi-modal human-computer interfaces; and multimedia databases. Many of his research ideas have been seminal, opening up new areas of research. Professor Huang is continuing his contribution to the field in the new millennium This book is intended to highlight his contributions by showing the breadth of areas in which his students are working. As such, contributed chapters were written by some of his many former graduate students (some with Professor Huang as a coauthor) and illustrate not only his contributions to imaging science but also his commitment to educational endeavor. The breadth of contributions is an indication of influence of Professor Huang to the field of signal processing, image processing, computer vision and applications; the book includes chapters on learning in image retrieval, facial motion analysis, cloud motion tracking, wavelet coding, robust video transmission, and many other topics. The Appendix contains several reprints of Professor Huang's most influential papers from 1970's to 1990's. This book is directed towards image processing researchers, including academic faculty, graduate students and industry researchers, as well as toward professionals working in application areas.

Advanced Image Processing Techniques and Applications

Advanced Image Processing Techniques and Applications
A Book

by Kumar, N. Suresh,Sangaiah, Arun Kumar,Arun, M.,Anand, S.

  • Publisher : IGI Global
  • Release : 2017-02-10
  • Pages : 439
  • ISBN : 1522520546
  • Language : En, Es, Fr & De
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Today, the scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Advanced Image Processing Techniques and Applications is an essential reference publication for the latest research on digital image processing advancements. Featuring expansive coverage on a broad range of topics and perspectives, such as image and video steganography, pattern recognition, and artificial vision, this publication is ideally designed for scientists, professionals, researchers, and academicians seeking current research on solutions for new challenges in image processing.