Improvement of Brain Tumor Feature based Segmentation using Decision based Alpha Trimmed Global Mean Filter

Detection of the brain tumor is an important application of medical image processing. The literature survey in this paper has shown that the many of the existing methods has unobserved the deprived quality images like images with amount of noise or poor brightness. Moreover the much of the existing work on tumor detection has abandoned the use of object based segmentation. The overall goal of this research work is to propose an efficient brain tumor detection using the feature detection androundness metric. To enhance the tumor detection rate further we have integrated the proposed object based tumor detection with the Decision based alpha trimmed global mean. The proposed technique has the ability to produce effective results even in case of high density of the noise.