Details
Classification in BioApps
Automation of Decision MakingLecture Notes in Computational Vision and Biomechanics, Band 26
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96,29 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 10.11.2017 |
| ISBN/EAN: | 9783319659817 |
| Sprache: | englisch |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<p>This book on classification in biomedical image applications presents original and valuable research work on advances in this field, which covers the taxonomy of both supervised and unsupervised models, standards, algorithms, applications and challenges.</p><p>Further, the book highlights recent scientific research on artificial neural networks in biomedical applications, addressing the fundamentals of artificial neural networks, support vector machines and other advanced classifiers, as well as their design and optimization.<br/></p><p>In addition to exploring recent endeavours in the multidisciplinary domain of sensors, the book introduces readers to basic definitions and features, signal filters and processing, biomedical sensors and automation of biomeasurement systems. The target audience includes researchers and students at engineering and medical schools, researchers and engineers in the biomedical industry, medical doctors and healthcare professionals. <br/></p><p></p>
Introduction to Medical Imaging and Objective Quality Assessment Techniques.- A Novel Approach for the Classification of Liver MR Images Using Complex Orthogonal Ripplet-II and Wavelet-Based Transforms.- ECG based Myocardial Infarction Detection using Hybrid Classification Techniques.- Machine Learning based Optical Plant Identification, Disease Detection and Disease Severity Assessment: State-of-the-Art .- Crop Disease Protection Using Parallel Machine Learning Approaches.- Deep Learning for Medical Image Processing: Overview, Challenges and Future.- On the Fly Segmentation of Intravascular Ultrasound Images Powered by Learning of Backscattering Physics.- ECG signal Dimensionality Reduction based Atrial Fibrillation Detection .- A Bio Application for Accident Victims’ Identification using Biometrics.
<b>Nilanjan Dey </b>is an Assistant Professor in the Department of Information Technology, Techno India College of Technology, Kolkata, W.B., India. He holds an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of Applied Mathematical Modeling in Human Physiology, Territorial Organization of- Scientific and Engineering Unions, Bulgaria. Associate Researcher of Laboratoire RIADI, University of Manouba, Tunisia. His research topic is Medical Imaging, Soft computing, Data mining, Machine learning, Rough set, Computer Aided Diagnosis, Atherosclerosis. He has 20 books and 300 international conferences and journal papers. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence (IGI Global), US, International Journal of Rough Sets and Data Analysis (IGI Global), US, the International Journal of Synthetic Emotions (IJSE), IGI Global, US, and International Journal of Natural Computing Research (IGI Global), US. Series Editor of Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, Executive Editor of International Journal of Image Mining (IJIM), Inderscience, and Associated Editor of IEEE Access journal and the International Journal of Service Science, Management, Engineering and Technology, IGI Global. He is a life member of IE, UACEE, ISOC.<div><br/></div><div><b>Amira S. Ashour</b> is currently an Assistant Professor and Head of Department-EEC, Faculty of Engineering, Tanta University, Egypt. She has been the Vice Chair of Computer Engineering Department, Computers and Information Technology College, Taif University, KSA for one year from 2015. She has been the vice chair of CS department, CIT college, Taif University, KSA for 5 years. Her research interests are Smart antenna, Direction of arrival estimation, Targets tracking, Image processing, Medical imaging, Machine learning, Signal/image/video processing, Image analysis, Computer vision, andOptimization. She has 6 books and about 70 published journal papers. She is an Editor-in-Chief for the International Journal of Synthetic Emotions (IJSE), IGI Global, US. She is an Associate Editor for the IJRSDA, IGI Global, US as well as the IJACI, IGI Global, US. She is an Editorial Board Member of the International Journal of Image Mining (IJIM), Inderscience.</div><div><br/></div><div><b>Surekha Borra</b> is currently a Professor in the Department of ECE, K. S. Institute of Technology, Bangalore, India. She earned her Doctorate in Image Processing from Jawaharlal Nehru Technological University, Hyderabad, India, in 2015. Her research interests are in the areas of Image and Video Analytics, Machine Learning, Biometrics and Remote Sensing. She has published several book chapters and research papers to her credit in refereed & indexed journals, and conferences at international and national levels. Her international recognition includes her professional memberships & services in refereed organizations, programme committees, editorial & review boards, wherein she has been a guest editor for 2 journals and reviewer for journals published by IEEE, IET, Elsevier, Taylor & Francis, Springer, IGI-Global etc,. She has received the Woman Achiever's Award from The Institution of Engineers (India), for her prominent research and innovative contributions, the Woman Educator & Scholar Award for her contributions to teaching and scholarly activities, and the Young Woman Achiever Award for her contribution in Copyright Protection of Images.</div>
<p>This book on classification in biomedical image applications presents original and valuable research work on advances in this field, which covers the taxonomy of both supervised and unsupervised models, standards, algorithms, applications and challenges.</p> <p>Further, the book highlights recent scientific research on artificial neural networks in biomedical applications, addressing the fundamentals of artificial neural networks, support vector machines and other advanced classifiers, as well as their design and optimization.<br/></p> In addition to exploring recent endeavours in the multidisciplinary domain of sensors, the book introduces readers to basic definitions and features, signal filters and processing, biomedical sensors and automation of biomeasurement systems. The target audience includes researchers and students at engineering and medical schools, researchers and engineers in the biomedical industry, medical doctors and healthcare professionals.<br/><p></p><p></p>
Provides broad background information on and solutions to existing challenges in classifiers used for biomedical applications Addresses various applications for the classification of biomedical signals from consumer and industry perspectives Highlights recent developments and topics of interest in machine learning techniques for the classification of biomedical signals Discusses the design and performance analysis of various existing classification techniques Includes standards for, challenges in, and recommendations for classifiers in biomedical applications Includes supplementary material: sn.pub/extras
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