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
Publsiher: Academic Press
Total Pages: 308
Release: 2020-08-11
ISBN 10: 0128192968
ISBN 13: 9780128192962
Language: EN, FR, DE, ES & NL

Advanced Machine Vision Paradigms for Medical Image Analysis Book Review:

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
Author: S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Publsiher: Academic Press
Total Pages: 458
Release: 2017-01-18
ISBN 10: 0128104090
ISBN 13: 9780128104095
Language: EN, FR, DE, ES & NL

Deep Learning for Medical Image Analysis Book Review:

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

Deep Learning in Healthcare

Deep Learning in Healthcare
Author: Yen-Wei Chen,Lakhmi C. Jain
Publsiher: Springer Nature
Total Pages: 218
Release: 2019-11-18
ISBN 10: 3030326063
ISBN 13: 9783030326067
Language: EN, FR, DE, ES & NL

Deep Learning in Healthcare Book Review:

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.

Computer Vision and Machine Intelligence in Medical Image Analysis

Computer Vision and Machine Intelligence in Medical Image Analysis
Author: Mousumi Gupta,Debanjan Konar,Siddhartha Bhattacharyya,Sambhunath Biswas
Publsiher: Springer Nature
Total Pages: 150
Release: 2019-08-28
ISBN 10: 9811387982
ISBN 13: 9789811387982
Language: EN, FR, DE, ES & NL

Computer Vision and Machine Intelligence in Medical Image Analysis Book Review:

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.

Soft Computing Based Medical Image Analysis

Soft Computing Based Medical Image Analysis
Author: Nilanjan Dey,Amira Ashour,Fuquian Shi,Valentina E. Balas
Publsiher: Academic Press
Total Pages: 292
Release: 2018-01-18
ISBN 10: 0128131748
ISBN 13: 9780128131749
Language: EN, FR, DE, ES & NL

Soft Computing Based Medical Image Analysis Book Review:

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

Advanced Computational Intelligence Paradigms in Healthcare 3

Advanced Computational Intelligence Paradigms in Healthcare   3
Author: Margarita Sordo,Sachin Vaidya
Publsiher: Springer
Total Pages: 257
Release: 2008-08-20
ISBN 10: 3540776621
ISBN 13: 9783540776628
Language: EN, FR, DE, ES & NL

Advanced Computational Intelligence Paradigms in Healthcare 3 Book Review:

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
Author: Margarita N. Favorskaya,Lakhmi C. Jain
Publsiher: Springer Nature
Total Pages: 321
Release: 2019-12-07
ISBN 10: 3030337952
ISBN 13: 9783030337957
Language: EN, FR, DE, ES & NL

Computer Vision in Advanced Control Systems 5 Book Review:

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.

Hybrid Machine Intelligence for Medical Image Analysis

Hybrid Machine Intelligence for Medical Image Analysis
Author: Siddhartha Bhattacharyya,Debanjan Konar,Jan Platos,Chinmoy Kar,Kalpana Sharma
Publsiher: Springer
Total Pages: 293
Release: 2020-08-21
ISBN 10: 9789811389320
ISBN 13: 9811389322
Language: EN, FR, DE, ES & NL

Hybrid Machine Intelligence for Medical Image Analysis Book Review:

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.

Natural User Interfaces in Medical Image Analysis

Natural User Interfaces in Medical Image Analysis
Author: Marek R. Ogiela,Tomasz Hachaj
Publsiher: Springer
Total Pages: 288
Release: 2014-06-07
ISBN 10: 3319078003
ISBN 13: 9783319078007
Language: EN, FR, DE, ES & NL

Natural User Interfaces in Medical Image Analysis Book Review:

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.

Riemannian Geometric Statistics in Medical Image Analysis

Riemannian Geometric Statistics in Medical Image Analysis
Author: Xavier Pennec,Stefan Sommer,Tom Fletcher
Publsiher: Academic Press
Total Pages: 636
Release: 2019-09-02
ISBN 10: 0128147261
ISBN 13: 9780128147269
Language: EN, FR, DE, ES & NL

Riemannian Geometric Statistics in Medical Image Analysis Book Review:

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

Computational Intelligence Paradigms in Advanced Pattern Classification

Computational Intelligence Paradigms in Advanced Pattern Classification
Author: Marek R. Ogiela,Lakhmi C. Jain
Publsiher: Springer Science & Business Media
Total Pages: 200
Release: 2012-01-13
ISBN 10: 3642240488
ISBN 13: 9783642240485
Language: EN, FR, DE, ES & NL

Computational Intelligence Paradigms in Advanced Pattern Classification Book Review:

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.

Computer Analysis of Images and Patterns

Computer Analysis of Images and Patterns
Author: Richard Wilson,Edwin Hancock,Adrian Bors,William Smith
Publsiher: Springer
Total Pages: 583
Release: 2013-08-17
ISBN 10: 3642402461
ISBN 13: 9783642402463
Language: EN, FR, DE, ES & NL

Computer Analysis of Images and Patterns Book Review:

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.

Pattern Recognition and Signal Analysis in Medical Imaging

Pattern Recognition and Signal Analysis in Medical Imaging
Author: Anke Meyer-Baese,Volker J. Schmid
Publsiher: Elsevier
Total Pages: 466
Release: 2014-03-21
ISBN 10: 0124166156
ISBN 13: 9780124166158
Language: EN, FR, DE, ES & NL

Pattern Recognition and Signal Analysis in Medical Imaging Book Review:

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

Advances in Soft Computing and Machine Learning in Image Processing

Advances in Soft Computing and Machine Learning in Image Processing
Author: Aboul Ella Hassanien,Diego Alberto Oliva
Publsiher: Springer
Total Pages: 718
Release: 2017-10-13
ISBN 10: 3319637541
ISBN 13: 9783319637549
Language: EN, FR, DE, ES & NL

Advances in Soft Computing and Machine Learning in Image Processing Book Review:

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.

Handbook of Medical Imaging

Handbook of Medical Imaging
Author: Anonim
Publsiher: Academic Press
Total Pages: 901
Release: 2000-10-09
ISBN 10: 9780080533100
ISBN 13: 0080533108
Language: EN, FR, DE, ES & NL

Handbook of Medical Imaging Book Review:

In recent years, the remarkable advances in medical imaging instruments have increased their use considerably for diagnostics as well as planning and follow-up of treatment. Emerging from the fields of radiology, medical physics and engineering, medical imaging no longer simply deals with the technology and interpretation of radiographic images. The limitless possibilities presented by computer science and technology, coupled with engineering advances in signal processing, optics and nuclear medicine have created the vastly expanded field of medical imaging. The Handbook of Medical Imaging is the first comprehensive compilation of the concepts and techniques used to analyze and manipulate medical images after they have been generated or digitized. The Handbook is organized in six sections that relate to the main functions needed for processing: enhancement, segmentation, quantification, registration, visualization as well as compression storage and telemedicine. * Internationally renowned authors(Johns Hopkins, Harvard, UCLA, Yale, Columbia, UCSF) * Includes imaging and visualization * Contains over 60 pages of stunning, four-color images

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

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications
Author: Exarchos, Themis P.,Papadopoulos, Athanasios,Fotiadis, Dimitrios I.
Publsiher: IGI Global
Total Pages: 598
Release: 2009-04-30
ISBN 10: 1605663158
ISBN 13: 9781605663159
Language: EN, FR, DE, ES & NL

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

"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.

Medical Image Recognition Segmentation and Parsing

Medical Image Recognition  Segmentation and Parsing
Author: S. Kevin Zhou
Publsiher: Academic Press
Total Pages: 542
Release: 2015-12-11
ISBN 10: 0128026766
ISBN 13: 9780128026762
Language: EN, FR, DE, ES & NL

Medical Image Recognition Segmentation and Parsing Book Review:

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

Advanced Biomedical Image Analysis

Advanced Biomedical Image Analysis
Author: Mark Haidekker
Publsiher: John Wiley & Sons
Total Pages: 540
Release: 2011-03-29
ISBN 10: 9781118099483
ISBN 13: 1118099486
Language: EN, FR, DE, ES & NL

Advanced Biomedical Image Analysis Book Review:

A comprehensive reference of cutting-edge advanced techniques for quantitative image processing and analysis Medical diagnostics and intervention, and biomedical research rely progressively on imaging techniques, namely, the ability to capture, store, analyze, and display images at the organ, tissue, cellular, and molecular level. These tasks are supported by increasingly powerful computer methods to process and analyze images. This text serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on biomedical applications. It offers both theory and practical examples for immediate application of the topics as well as for in-depth study. Advanced Biomedical Image Analysis presents methods in the four major areas of image processing: image enhancement and restoration, image segmentation, image quantification and classification, and image visualization. In each instance, the theory, mathematical foundation, and basic description of an image processing operator is provided, as well as a discussion of performance features, advantages, and limitations. Key algorithms are provided in pseudo-code to help with implementation, and biomedical examples are included in each chapter. Image registration, storage, transport, and compression are also covered, and there is a review of image analysis and visualization software. The accompanying live DVD contains a selection of image analysis software, and it provides most of the algorithms from the book so readers can immediately put their new knowledge to use. Members of the academic community involved in image-related research as well as members of the professional R&D sector will rely on this volume. It is also well suited as a textbook for graduate-level image processing classes in the computer science and engineering fields.

Handbook of Medical Imaging Medical image processing and analysis

Handbook of Medical Imaging  Medical image processing and analysis
Author: Jacob Beutel,Milan Sonka,Harold L. Kundel,Richard L. Van Metter,J. Michael Fitzpatrick
Publsiher: SPIE Press
Total Pages: 1218
Release: 2000
ISBN 10: 9780819436221
ISBN 13: 0819436224
Language: EN, FR, DE, ES & NL

Handbook of Medical Imaging Medical image processing and analysis Book Review:

Volume 2 addresses the methods in use or in development for enhancing the visual perception of digital medical images obtained by a wide variety of imaging modalities and for image analysis as an aid to detection and diagnosis.

Advancement of Machine Intelligence in Interactive Medical Image Analysis

Advancement of Machine Intelligence in Interactive Medical Image Analysis
Author: Om Prakash Verma,Sudipta Roy,Subhash Chandra Pandey,Mamta Mittal
Publsiher: Springer Nature
Total Pages: 329
Release: 2019-12-11
ISBN 10: 9811511004
ISBN 13: 9789811511004
Language: EN, FR, DE, ES & NL

Advancement of Machine Intelligence in Interactive Medical Image Analysis Book Review:

The book discusses major technical advances and research findings in the field of machine intelligence in medical image analysis. It examines the latest technologies and that have been implemented in clinical practice, such as computational intelligence in computer-aided diagnosis, biological image analysis, and computer-aided surgery and therapy. This book provides insights into the basic science involved in processing, analysing, and utilising all aspects of advanced computational intelligence in medical decision-making based on medical imaging.