Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques
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 and intuitionistic fuzzy aggregation operators, and distance and similarity measures
- Covers medical image enhancement using advanced fuzzy sets, including MATLAB-based examples to increase the contrast of the images
- Describes intuitionistic fuzzy and Type II fuzzy thresholding techniques that separate different regions, leukocyte types, and abnormal lesions
- Demonstrates the clustering of unwanted lesions and 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.
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