Hybridization of Fuzzy and Region Growing Segmentation based Tumor detection using trilateral filter

The brain tumor detection is a critical application of medical image processing. The literature survey has shown that probably the most of existing methods has ignored the indigent quality images like images which are of poor brightness or with noise. In addition, the most of the existing work on tumor detection has neglected the utilization of object-based segmentation. The overall goal of this research work is to propose an efficient brain tumor detection using the feature detection and roundness metric. To enhance the tumor detection rate further we have integrated the proposed hybridization of fuzzy and region growing segmentation based tumor detection with the trilateral filter. The proposed technique has the ability to produce effective results even in case of high density of the noise. The experimental results have clearly shown that the proposed technique outperforms over the available techniques.