Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques
Language: English
Published by Taylor & Francis Inc, 2015
- Hardcover
- New

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'Medical Image Processing' deals with the application of intuitionistic fuzzy and Type II fuzzy set theories for medical image analysis. Designed for graduate and doctorate students, it provides a brief introduction to advanced fuzzy set theory. Num Pages: 236 pages, 182 black & white illustrations, 1 black & white tables. BIC Classification: MQW; TJFM; UYT. Category: (G) General (US: Trade). Dimension: 244 x 164 x 18. Weight in Grams: 474. . 2015. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
Seller Inventory # V9781498700450
- Title
- Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques
- Author
- Tamalika Chaira
- Publisher
- Taylor & Francis Inc
- Publication year
- 2015
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1498700454
- ISBN 13
- 9781498700450
Medical image analysis using advanced fuzzy set theoretic techniques is an exciting and dynamic branch of image processing. Since the introduction of fuzzy set theory, there has been an explosion of interest in advanced fuzzy set theories―such as intuitionistic fuzzy and Type II fuzzy set―that represent uncertainty in a better way.
Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques deals with the application of intuitionistic fuzzy and Type II fuzzy set theories for medical image analysis. Designed for graduate and doctorate students, this higher-level text:
- Provides a brief introduction to advanced fuzzy set theory, fuzzy/intuitionistic fuzzy aggregation operators, and distance/similarity measures
- Covers medical image enhancement using advanced fuzzy sets, including MATLAB®-based examples to increase contrast of the images
- Describes intuitionistic fuzzy and Type II fuzzy thresholding techniques that separate different regions/leukocyte types/abnormal lesions
- Demonstrates the clustering of unwanted lesions/regions even in the presence of noise by applying intuitionistic fuzzy clustering
- Highlights the edges of poorly illuminated images and uses intuitionistic fuzzy edge detection to find the edges of different regions
- Defines fuzzy mathematical morphology and explores its application using the Lukasiewicz operator, t-norms, and t-conorms
Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques is useful not only for students, but also for teachers, engineers, scientists, and those interested in the field of medical image analysis. A basic knowledge of fuzzy set is required, along with a solid understanding of mathematics and image processing.
"Synopsis" may belong to another edition of this title.
About the Author
Tamalika Chaira is a research scientist in the Department of Biotechnology, Government of India, and the Indian Institute of Technology Delhi, New Delhi. Previously, she was a research associate at the National Research Council (CNR), Pisa, Italy. She holds a bachelor’s degree from Bihar Institute of Technology, Sindri, Jharkhand, India; a master’s degree from Bengal Engineering and Science University, Shibpur, Howrah, India; and a Ph.D from the Indian Institute of Technology, Kharagpur, West Bengal. She is an author of the book Fuzzy Image Processing and Applications with MATLAB, as well as numerous papers. She also received the prestigious National Award (Innovative Young Biotechnologist Award, 2010) from the Government of India.
"About the title" may belong to another edition of this title.
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