MRI Brain Abnormality Detection Using Fuzzy Neural Network
Price
Free (open access)
Volume
16
Pages
7
Published
1996
Size
118 kb
Paper DOI
10.2495/AI960241
Copyright
WIT Press
Author(s)
Kasra Haghighi
Abstract
In this paper an expert system for detection of brain abnormalities is proposed. First preceding methods for segmentation of MR images are reviewed and their limitations are discussed. In the proposed method, MR images (three images from one slice: T1, T2 and Proton Density) are acquired from a scanner or directly from MRI system. For noise deletation two filters (median and bandreject lowpass) are used (This stage is optional). They make a clean view of MR images. It is necessary to have precise detections. So by implementing a gray-scale to color transformation algorithm (it is a radially symmetric butterworth band-reject filter), system can recognize the differences between tissues accurately. Now we have three colored images (T1, T2 and Proton Density) from the last section that better represent tissues and it is possible to say that those tissues with the s
Keywords