Background: Medical imaging plays a key role in detecting and diagnosing abnormal
patterns from scanned images. The computer aided automatic detection of the brain tumor was proposed
in this work using Adaptive Neuro Fuzzy Inference System (ANFIS) classifier.
Methods: The proposed system has the following stages as noise reduction, Gabor transform, feature
extraction and ANFIS classifier. The impulse noises in the brain images were detected and removed
using directional filtering algorithm. Gabor transform transformed the spatial domain image
into multi resolution image and further Pixel invariant, Local Binary Pattern (LBP) and Discrete
Wavelet Transform (DWT) features were extracted from the Gabor transformed image and these
features were given to the ANFIS classifier to classify the image as either normal and abnormal.
Discussion: The morphological operations were then applied over the abnormal image to segment
the tumor regions.
Conclusion: The proposed system achieved 99.8%sensitivity, 99.7%specificity, and 99.8% accuracy
for the brain tumor detection.