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Authors
Affiliations
1 Department of Information Science and Technology, College of Engineering, Guindy, IN
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 3, No 4 (2011), Pagination: 45-55
Abstract
This paper proposes a complete framework based on fuzzy logic, for the retrieval of MRI images of the brain. In our system, the MRI image is segmented using the fuzzy local information c means (FLICM) algorithm. Region, location and shape properties are extracted from each region. These properties are represented as fuzzy features. Thus each image is represented by a set of fuzzy features corresponding to the various regions obtained after segmentation. To compute the overall similarity between two images, unified feature matching (UFM) is used. This measure integrates the properties of all the regions in an image. Our system can be applied to distinguish between the tumor and normal magnetic resonance images. Also the location feature of each region, especially of the tumor region, obtained after segmentation can be used to determine the type and symptoms of the brain tumor. Images from the brain web were used for experimentation.
Keywords
Fuzzy Logic, Segmentation, Clustering, Feature Matching, Fuzzy Similarity.
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