Abstract
A segmentation algorithm of brain tumor MR image based on Tamura texture feature and BP Neural Network is proposed in this paper. Firstly, the local grayscale features of four modal MR images are combined with the Tamura texture metrics in the algorithm. The information in the image is extracted as much as possible. Then, the known samples are input into the BP Neural Network and classifier training is performed. Finally, other brain tumor images are processed with the trained BP Neural Network. The experiment was performed on the images of 30 patients. From the obtained data, the method proposed in this paper can segment the brain tumor region accurately and effectively and show strong self-adaptability to the difference of the brain tumor images.
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