08-16-2017, 11:58 PM
brain tumor detection using matlab sample code
Abnormal cell growth leads to tumour in the brain cells. Earlier detection,diagnosis and proper treatment of brain tumour are essential to prevent human death. An effective brain tumour segmentation of MR image is an essential task in medical field. Extracting or grouping of pixels in an image based on intensity values is called segmentation. Image segmentation can be achieved in different ways those are thresholding, region growing, water sheds and contours. The drawbacks of previous methods can be overcome through proposed method. To extract information regarding tumour, at first in the pre-processing level, the extra parts which are outside the skull and don't have any helpful information are removed and then anisotropic diffusion
filter is applied to the MRI images to remove noise. By applying the fast bounding box (FBB) algorithm, the tumour area is displayed on the MRI image with a bounding box and the central part is selected as sample points for training of a One Class SVM classifier. Then Support Vector Machine classifies the boundary and extracts the tumour. This method can be implemented by MATLAB. Experimental results show high precision and dependability of the proposed algorithm. The results are also highly helpful for specialists and radiologists to easily estimate the size and position of a tumour.