AIRCC's International Journal of Computer Science and Information Technology

The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).

If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Fullscreen Fullscreen Off


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.
User
Notifications
Font Size