A feature extraction approach in medical magnetic resonance imaging (MRI) is proposed. In this approach, first the combination of spatial filters using the 5×5 wiener filter followed by a 3×3 Gaussian filter is used to remove the noisy pixels while preserving the important information. Next, the edge detection algorithm based on multiple-scales edge detection of Gabor filters is applied. Moreover, Wavelet transform based image fusion is used to combine the detail coefficients. Finally, the nonmaxima suppression technique is adopted to get the final result. The experiments show that the proposed algorithm can be detected well-localized, and thin edges. Therefore, the algorithm leads to a useful method for feature extraction in MRI images and can be used for diagnostic purposes.
