Abstract

This chapter discusses the application of fuzzy set and intuitionistic fuzzy set theory in medical image processing. Different types of fuzzy membership functions, fuzzy operators, fuzzy measures, fuzzy integrals, and entropy are used in processing these images. Processing includes enhancement, segmentation, retrieval, clustering, and edge detection. There are two types of images – analog images and digital images. Preprocessing is required in almost all medical images. Enhancement increases the overall visual contrast of the image so that the image structures are more clear and distinguishable. The chapter also discusses few results on enhancement of medical images using fuzzy and intuitionistic fuzzy set theory. Segmentation is a fundamental building block in image analysis. Thresholding is a type of segmentation that is computationally fast and an inexpensive segmentation technique. Edge‐based segmentation is a type of segmentation that determines the boundaries of the image regions such as organ structures/abnormalities in medical images.

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