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Medical Image Processing
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Table of Contents

Intuitionistic Fuzzy Set and Type II Fuzzy Set. Medical Image Processing. Fuzzy and Intuitionistic Fuzzy Operators with Application in Decision-Making. Similarity, Distance Measures, and Entropy. Image Enhancement. Thresholding of Medical Images. Clustering of Medical Images. Edge Detection. Fuzzy Mathematical Morphology.

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.

Reviews

"The book treats the most commonly used fuzzy methods in medical image analysis. It does focus on widely used approaches and refrains from methods, which are still under investigations. This increases its value for practitioners, senior students and young researchers… Clearly. The book has been written by a dedicated professional (I do not know the author and have never met her). It should be on the desk of everybody who works on medical image analysis and researching the potentials of fuzzy systems."
—Hamid R. Tizhoosh, Affiliation: University of Waterloo, Canada"This book focuses on the application of clustering algorithms based on intuitionistic fuzzy set model [s]and their application in segmenting and analyzing medical images. …I would like to keep a copy of the book on my shelf.
—Dr.B.K.Tripathy, VIT University, India"Among the characteristics that make the book Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques a valuable addition to the library of both the medical image processing student and the experienced practitioner, is the detailed and self-contained nature of the subjects treated in each one of the chapters of the book. Moreover, the examples that accompany the theoretical notions of the book, as well as the MATLAB code supporting the applications of fuzzy sets in the area of medical image processing, are of paramount importance for both the novice and the experienced reader.
—Ioannis K. Vlachos, School of Electrical and Computer Engineering National Technical University of Athens

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