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

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: 2019-08-08
ISBN 10: 9811389306
ISBN 13: 9789811389306
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.

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.

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.

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.

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

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 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.

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

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

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.

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

Computational Retinal Image Analysis

Computational Retinal Image Analysis
Author: Emanuele Trucco,Tom MacGillivray,Yanwu Xu
Publsiher: Academic Press
Total Pages: 502
Release: 2019-11-25
ISBN 10: 0081028172
ISBN 13: 9780081028179
Language: EN, FR, DE, ES & NL

Computational Retinal Image Analysis Book Review:

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

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.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Lia Morra,Silvia Delsanto,Loredana Correale
Publsiher: CRC Press
Total Pages: 152
Release: 2019-11-25
ISBN 10: 1000753085
ISBN 13: 9781000753080
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medical Imaging Book Review:

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 and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective

Hybrid Computational Intelligence

Hybrid Computational Intelligence
Author: Siddhartha Bhattacharyya,Vaclav Snasel,Deepak Gupta,Ashish Khanna
Publsiher: Academic Press
Total Pages: 250
Release: 2020-03-05
ISBN 10: 012818700X
ISBN 13: 9780128187005
Language: EN, FR, DE, ES & NL

Hybrid Computational Intelligence Book Review:

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 hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. Provides insights into the latest research trends in hybrid intelligent algorithms and architectures Focuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interaction Features hybrid intelligent applications in biomedical engineering and healthcare informatics

Computational Vision and Bio Inspired Computing

Computational Vision and Bio Inspired Computing
Author: S. Smys,João Manuel R. S. Tavares,Valentina Emilia Balas,Abdullah M. Iliyasu
Publsiher: Springer Nature
Total Pages: 1413
Release: 2020-01-06
ISBN 10: 3030372189
ISBN 13: 9783030372187
Language: EN, FR, DE, ES & NL

Computational Vision and Bio Inspired Computing Book Review:

This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. Due to the rapid advances in the emerging information, communication and computing technologies, the Internet of Things, cloud and edge computing, and artificial intelligence play a significant role in the computational vision context. In recent years, computational vision has contributed to enhancing the methods of controlling the operations in biological systems, like ant colony optimization, neural networks, and immune systems. Moreover, the ability of computational vision to process a large number of data streams by implementing new computing paradigms has been demonstrated in numerous studies incorporating computational techniques in the emerging bio-inspired models. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization, and big data modeling and management, that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems, and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

Algorithms for Image Processing and Computer Vision

Algorithms for Image Processing and Computer Vision
Author: J. R. Parker
Publsiher: John Wiley & Sons
Total Pages: 504
Release: 2010-11-29
ISBN 10: 9781118021880
ISBN 13: 1118021886
Language: EN, FR, DE, ES & NL

Algorithms for Image Processing and Computer Vision Book Review:

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
Author: Marek R. Ogiela,Lakhmi C Jain
Publsiher: Springer
Total Pages: 199
Release: 2012-01-13
ISBN 10: 3642240496
ISBN 13: 9783642240492
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.

Academic Press Library in Signal Processing Volume 6

Academic Press Library in Signal Processing  Volume 6
Author: Anonim
Publsiher: Academic Press
Total Pages: 458
Release: 2017-11-28
ISBN 10: 0128119004
ISBN 13: 9780128119006
Language: EN, FR, DE, ES & NL

Academic Press Library in Signal Processing Volume 6 Book Review:

Academic Press Library in Signal Processing, Volume 6: Image and Video Processing and Analysis and Computer Vision is aimed at university researchers, post graduate students and R&D engineers in the industry, providing a tutorial-based, comprehensive review of key topics and technologies of research in both image and video processing and analysis and computer vision. The book provides an invaluable starting point to the area through the insight and understanding that it provides. With this reference, readers will quickly grasp an unfamiliar area of research, understand the underlying principles of a topic, learn how a topic relates to other areas, and learn of research issues yet to be resolved. Presents a quick tutorial of reviews of important and emerging topics of research Explores core principles, technologies, algorithms and applications Edited and contributed by international leading figures in the field Includes comprehensive references to journal articles and other literature upon which to build further, more detailed knowledge