An Approach to Brain Tumor MR Image Detection and Classification using Neuro Fuzzy
DOI:
https://doi.org/10.11113/jt.v61.1627Keywords:
ANFIS, MRI, brain tumor, segmentation, classificationAbstract
Segmentation is an important step in many applications, being also important in those that deal with medical images. Thresholding is one of the most important and used techniques for image segmentation. Some segmentation techniques based on thresholding are performed in order to segment the tumors. The conventional method used in medicine for brain magnetic resonance (MR) images classification and tumors detection is by human inspection. The use of artificial intelligent techniques, for instance, neural networks, fuzzy logic and neuro fuzzy have shown great potential in this field. Hence, in this study, the neuro fuzzy system or ANFIS is applied for classification purposes. ANFIS is applied to classify the abnormal brain based on the location of the tumors. The performance of the ANFIS classifier is evaluated in terms of training performance and classification accuracy and the results confirmed that the proposed ANFIS classifier has potential in classifying the tumors.References
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