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Soft Computing Based Medical Image Analysis


Soft Computing Based Medical Image Analysis
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Soft Computing Based Medical Image Analysis


Soft Computing Based Medical Image Analysis
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2018-01-18

Soft Computing Based Medical Image Analysis written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-18 with Technology & Engineering categories.


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



Hybrid Machine Intelligence For Medical Image Analysis


Hybrid Machine Intelligence For Medical Image Analysis
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Author : Siddhartha Bhattacharyya
language : en
Publisher: Springer
Release Date : 2019-08-08

Hybrid Machine Intelligence For Medical Image Analysis written by Siddhartha Bhattacharyya and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-08 with Technology & Engineering categories.


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.



Neutrosophic Set In Medical Image Analysis


Neutrosophic Set In Medical Image Analysis
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Author : Yanhui Guo
language : en
Publisher: Academic Press
Release Date : 2019-08-08

Neutrosophic Set In Medical Image Analysis written by Yanhui Guo and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-08 with Computers categories.


Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set's novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis. - Introduces the mathematical model and concepts of neutrosophic theory and methods - Highlights the different techniques of neutrosophic theory, focusing on applying the neutrosophic set in image analysis to support computer- aided diagnosis (CAD) systems, including approaches from soft computing and machine learning - Shows how NS techniques can be applied to medical image denoising, segmentation and classification - Provides challenges and future directions in neutrosophic set based medical image analysis



Soft Computing In Image Processing


Soft Computing In Image Processing
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Author : Mike Nachtegael
language : en
Publisher: Springer
Release Date : 2007-06-24

Soft Computing In Image Processing written by Mike Nachtegael and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-24 with Technology & Engineering categories.


Images have always been very important in human life. Their applications range from primitive communication between humans of all ages to advanced technologies in the industrial, medical and military field. The increased possibilities to capture and analyze images have contributed to the largeness that the scientific field of "image processing" has become today. Many techniques are being applied, including soft computing. "Soft Computing in Image Processing: Recent Advances" follows the edited volumes "Fuzzy Techniques in Image Processing" (volume 52, published in 2000) and "Fuzzy Filters for Image Processing" (volume 122, published in 2003), and covers a wide range of both practical and theoretical applications of soft computing in image processing. The 16 excellent chapters of the book have been grouped into five parts: Applications in Remote Sensing, Applications in Image Retrieval, Applications in Image Analysis, Other Applications, and Theoretical Contributions. The focus of the book is on practical applications, which makes it interesting for every researcher that is involved with soft computing, image processing, or both scientific branches.



Intelligent Systems


Intelligent Systems
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Author : Chiranji Lal Chowdhary
language : en
Publisher: CRC Press
Release Date : 2020-01-06

Intelligent Systems written by Chiranji Lal Chowdhary and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-06 with Business & Economics categories.


This volume helps to fill the gap between data analytics, image processing, and soft computing practices. Soft computing methods are used to focus on data analytics and image processing to develop good intelligent systems. To this end, readers of this volume will find quality research that presents the current trends, advanced methods, and hybridized techniques relating to data analytics and intelligent systems. The book also features case studies related to medical diagnosis with the use of image processing and soft computing algorithms in particular models. Providing extensive coverage of biometric systems, soft computing, image processing, artificial intelligence, and data analytics, the chapter authors discuss the latest research issues, present solutions to research problems, and look at comparative analysis with earlier results. Topics include some of the most important challenges and discoveries in intelligent systems today, such as computer vision concepts and image identification, data analysis and computational paradigms, deep learning techniques, face and speaker recognition systems, and more.



Computational Intelligence And Soft Computing Applications In Healthcare Management Science


Computational Intelligence And Soft Computing Applications In Healthcare Management Science
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Author : Gul, Muhammet
language : en
Publisher: IGI Global
Release Date : 2020-03-06

Computational Intelligence And Soft Computing Applications In Healthcare Management Science written by Gul, Muhammet and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-06 with Medical categories.


In today’s modernized world, the field of healthcare has seen significant practical innovations with the implementation of computational intelligence approaches and soft computing methods. These two concepts present various solutions to complex scientific problems and imperfect data issues. This has made both very popular in the medical profession. There are still various areas to be studied and improved by these two schemes as healthcare practices continue to develop. Computational Intelligence and Soft Computing Applications in Healthcare Management Science is an essential reference source that discusses the implementation of soft computing techniques and computational methods in the various components of healthcare, telemedicine, and public health. Featuring research on topics such as analytical modeling, neural networks, and fuzzy logic, this book is ideally designed for software engineers, information scientists, medical professionals, researchers, developers, educators, academicians, and students.



Soft Computing For Recognition Based On Biometrics


Soft Computing For Recognition Based On Biometrics
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Author : Patricia Melin
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-20

Soft Computing For Recognition Based On Biometrics written by Patricia Melin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-20 with Computers categories.


This book describes bio-inspired models and applications of hybrid intelligent systems using soft computing techniques for image analysis and pattern recognition based on biometrics and other sources. Each section groups papers on a similar subject.



Deep Neural Networks For Multimodal Imaging And Biomedical Applications


Deep Neural Networks For Multimodal Imaging And Biomedical Applications
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Author : Suresh, Annamalai
language : en
Publisher: IGI Global
Release Date : 2020-06-26

Deep Neural Networks For Multimodal Imaging And Biomedical Applications written by Suresh, Annamalai and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-26 with Computers categories.


The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques. Deep Neural Networks for Multimodal Imaging and Biomedical Applications provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging. Featuring coverage on a broad range of topics such as prediction models, edge computing, and quantitative measurements, this book is ideally designed for researchers, academicians, physicians, IT consultants, medical software developers, practitioners, policymakers, scholars, and students seeking current research on biomedical advancements and developing computational methods in healthcare.



Soft Computing Applications And Techniques In Healthcare


Soft Computing Applications And Techniques In Healthcare
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Author : Ashish Mishra
language : en
Publisher: CRC Press
Release Date : 2020-10-09

Soft Computing Applications And Techniques In Healthcare written by Ashish Mishra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-09 with Computers categories.


This book provides insights into contemporary issues and challenges in soft computing applications and techniques in healthcare. It will be a useful guide to identify, categorise and assess the role of different soft computing techniques for disease, diagnosis and prediction due to technological advancements. The book explores applications in soft computing and covers empirical properties of artificial neural network (ANN), evolutionary computing, fuzzy logic and statistical techniques. It presents basic and advanced concepts to help beginners and industry professionals get up to speed on the latest developments in soft computing and healthcare systems. It incorporates the latest methodologies and challenges facing soft computing, examines descriptive, predictive and social network techniques and discusses analytics tools and their role in providing effective solutions for science and technology. The primary users for the book include researchers, academicians, postgraduate students, specialists and practitioners. Dr. Ashish Mishra is a professor in the Department of Computer Science and Engineering, Gyan Ganga Institute of Technology and Sciences, Jabalpur, Madhya Pradesh, India. He has contributed in organising the INSPIRE Science Internship Camp. He is a member of the Institute of Electrical and Electronics Engineers and is a life member of the Computer Society of India. His research interests include the Internet of Things, data mining, cloud computing, image processing and knowledge-based systems. He holds nine patents in Intellectual Property, India. He has authored four books in the areas of data mining, image processing and LaTex. Dr. G. Suseendran is an assistant professor, Department of Information Technology, School of Computing Sciences, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, Tamil Nadu, India. His research interests include ad-hoc networks, the Internet of Things, data mining, cloud computing, image processing, knowledge-based systems, and Web information exploration. He has published more than 75 research papers in various international journals such as Science Citation Index, Springer Book Chapter, Scopus, IEEE Access and UGC-referred journals. Prof. Trung-Nghia Phung is an associate professor and Head of Academic Affairs, Thai Nguyen University of Information and Communication Technology (ICTU). He has published more than 60 research papers. His main research interest lies in the field of speech, audio, and biomedical signal processing. He serves as a technical committee program member, track chair, session chair, and reviewer of many international conferences and journals. He was a co-Chair of the International Conference on Advances in Information and Communication Technology 2016 (ICTA 2016) and a Session Chair of the 4th International Conference on Information System Design and Intelligent Applications (INDIA 2017).



Soft Computing For Image Processing


Soft Computing For Image Processing
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Author : Sankar K. Pal
language : en
Publisher: Physica
Release Date : 2013-03-19

Soft Computing For Image Processing written by Sankar K. Pal and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-19 with Computers categories.


Any task that involves decision-making can benefit from soft computing techniques which allow premature decisions to be deferred. The processing and analysis of images is no exception to this rule. In the classical image analysis paradigm, the first step is nearly always some sort of segmentation process in which the image is divided into (hopefully, meaningful) parts. It was pointed out nearly 30 years ago by Prewitt (1] that the decisions involved in image segmentation could be postponed by regarding the image parts as fuzzy, rather than crisp, subsets of the image. It was also realized very early that many basic properties of and operations on image subsets could be extended to fuzzy subsets; for example, the classic paper on fuzzy sets by Zadeh [2] discussed the "set algebra" of fuzzy sets (using sup for union and inf for intersection), and extended the defmition of convexity to fuzzy sets. These and similar ideas allowed many of the methods of image analysis to be generalized to fuzzy image parts. For are cent review on geometric description of fuzzy sets see, e. g. , [3]. Fuzzy methods are also valuable in image processing and coding, where learning processes can be important in choosing the parameters of filters, quantizers, etc.