Brain Tumor Extraction from MRI Using Clustering Methods and Evaluation of Their Performance

In this paper, we consider the extraction of brain tumor from MRI (Magnetic Resonance Imaging) images using K-means, Fuzzy c-means and Region growing clustering methods. After extraction, various parameters related to performance of clustering methods, and also, parameters related to description of tumor are calculated. MRI is a non-invasive method which provides the view of structural features of tissues in the body at very high resolution (typically on $100 \mu \text{m}$ scale). Therefore, it will be advantageous if the detection and segmentation of brain tumors are based on MRI. This work is in the direction of replacing the manual identification and separation of tumor structures from brain MRI by computer aided techniques, which would add great value with respect to accuracy, reproducibility, diagnosis and treatment planning. The brain tumor separated from original image is referred as Region of Interest (ROI) and remaining portion of original image is referred as Non-region of Interest (NROI).

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