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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis (Advances in ubiquitous sensing applications for healthcare, Volume 4) - Softcover

Dey

 
9780128180044: Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis (Advances in ubiquitous sensing applications for healthcare, Volume 4)
Softcover
ISBN 10: 0128180048 ISBN 13: 9780128180044
Verlag: Academic Press, 2019

Inhaltsangabe

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images.

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Über die Autorin bzw. den Autor

Nilanjan Dey (Senior Member, IEEE) received the B.Tech., M.Tech. in information technology from West Bengal Board of Technical University and Ph.D. degrees in electronics and telecommunication engineering from Jadavpur University, Kolkata, India, in 2005, 2011, and 2015, respectively. Currently, he is Associate Professor with the Techno International New Town, Kolkata and a visiting fellow of the University of Reading, UK. He has authored over 300 research articles in peer-reviewed journals and international conferences and 40 authored books. His research interests include medical imaging and machine learning. Moreover, he actively participates in program and organizing committees for prestigious international conferences, including World Conference on Smart Trends in Systems Security and Sustainability (WorldS4), International Congress on Information and Communication Technology (ICICT), International Conference on Information and Communications Technology for Sustainable Development (ICT4SD) etc.

He is also the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, Associate Editor of IEEE Transactions on Technology and Society and series Co-Editor of Springer Tracts in Nature-Inspired Computing and Data-Intensive Research from Springer Nature and Advances in Ubiquitous Sensing Applications for Healthcare from Elsevier etc. Furthermore, he was an Editorial Board Member Complex & Intelligence Systems, Springer, Applied Soft Computing, Elsevier and he is an International Journal of Information Technology, Springer, International Journal of Information and Decision Sciences etc. He is a Fellow of IETE and member of IE, ISOC etc.

Von der hinteren Coverseite

Classification in Clinical Applications covers the most current advances in applying classification techniques to a wide variety of clinical applications, appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management, and computer aided diagnosis (CAD) systems design. Classification techniques are used for medical image analysis as a part of computer aided diagnosis systems, which employ machine learning, data analysis, pattern recognition and other deep learning techniques. Classification is an important statistical/mathematical tool used to refine and analyze complex systems such as medical images. The clinical applications can be across a wide range of diseases/procedures/specialties and are included as examples in the book. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN), and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images because they contain tools for data pre-processing, classification, regression, clustering, association rules and visualization.

Medical image classification is essential for accurate diagnosis and development of computer aided diagnosis (CAD) systems in clinical applications. For physicians, automated classification of medical images is an increasingly significant tool in their daily activity. Advances in medical imaging technology supported by computer science have enhanced interpretation of medical images and contributed to early diagnosis. The development of CAD systems provides a method of assisting physicians in the detection of abnormalities, quantification of disease progress and alternate diagnosis of lesions. Extraction of appropriate features is a vital step in any image classification. Furthermore, since medical images are often highly textured, texture analysis becomes crucial in medical image analysis.

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Verlag
Academic Press
Erscheinungsdatum
2019
Sprache
Englisch
ISBN 10 
0128180048
ISBN 13 
9780128180044
Einband
Taschenbuch
Anzahl der Seiten
218
Kontakt zum Hersteller
Academic Press
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