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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
Researchers and graduate students working in medical imaging, image analysis, computer vision
1. Introduction to neutrosophy and neutrosophic environment
2. Advanced neutrosophic sets in Microscopic Image Analysis
3. Advanced neutrosophic set-based ultrasound image analysis
4. Neutrosophic set in medical image denoising
5. Advanced optimization-based neutrosophic sets for medical image denoising
6. Neutrosophic set-based denoising of optical coherence tomography images
7. A survey on neutrosophic medical image segmentation
8. Neutrosophic set in medical image clustering
9. Optimization-based neutrosophic set for medical image processing
10. Neutrosophic hough transform for blood cells nuclei detection
11. Neutrosophic sets in dermoscopic medical image segmentation
12. Neutrosophic similarity score-based entropy measure for focal and nonfocal electroencephalogram signal classification
13. Neutrosophic multiple deep convolutional neural network for skin dermoscopic image classification
14. Neutrosophic set-based deep learning in mammogram analysis
15. Challenges and future directions in neutrosophic set-based medical image analysis
- No. of pages:
- © Academic Press 2019
- 9th August 2019
- Academic Press
- Paperback ISBN:
- eBook ISBN:
Yanhui Guo is currently an Assistant professor in the Department of Computer Science at the University of Illinois at Springfield, USA. He received his B. S. degree in Automatic Control from Zhengzhou University, China, M.S. degree in Pattern Recognition and Intelligence System from Harbin Institute of Technology, China, and Ph.D. degree in the Department of Computer Science, Utah State University, USA. Dr. Guo has published more than 80 journal papers and 30 top conference papers, completed 11 grant funded research projects, and worked as an associate editor of different international journals, reviewers for top journals and conferences. His research area includes neutrosophic theory, computer vision, machine learning, big data analytics, computer aided detection/diagnosis, and computer assist surgery.
Assistant Professor, Department of Computer Science, University of Illinois, Springfield, USA
Amira S. Ashour is an Assistant Professor and Head of Electronics and Electrical Communications Engineering Department, Faculty of Engineering, Tanta University, Egypt. She is a member in the Research and Development Unit, Faculty of Engineering, Tanta University, Egypt. She received the B.Eng. degree in Electrical Engineering from Faculty of Engineering, Tanta University, Egypt in 1997, M.Sc. in Image Processing in 2001 and Ph.D. in Smart Antenna in 2005 from Faculty of Engineering, Tanta University, Egypt. Ashour 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, Biomedical Systems, Pattern recognition, Image analysis, Computer vision, Computer-aided detection and diagnosis systems, Optimization, and Neutrosophic theory. She has 15 books and about 150 published journal papers. She is an Editor-in-Chief for the International Journal of Synthetic Emotions (IJSE), IGI Global, US.
Assistant Professor and Head of Electronics and Electrical Communications Engineering Department, Faculty of Engineering, Tanta University, Egypt
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