In medical image processing, image fusion technique is used to enhance
the brain tumors or inertial component of the brain for better medical diagnosis and
further clinical treatment. In this paper, the brain tumor is detected and diagnosed
by the following stages; preprocessing, fuzzy logic based fusion, feature extraction,
Genetic algorithm and classification. Mamdani Fuzzy rules are constructed
and used for brain tumor enhancement. Local binary and ternary pattern are extracted
from the fused image and best features are selected by genetic algorithm.
The extracted features are trained and classified into normal or abnormal brain image
by feed forward back propagation neural networks. Morphological operations
are used to segment the brain tumor from the classified brain image. The methodology
presented in this paper is tested over the images available from the public datasets. The proposed
system achieved the sensitivity rate of 99.67%, specificity rate of 99.56% and accuracy of
Keywords: Cerebral MRI images, fuzzy logic, image fusion, medical image, mathematical morphology, tumor.
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