Research On Segmentation Of Brain Tumor Base On Active Contour Model

Since the recent 20 years, the technology of diagnosis and treatment on brain tumor evolved for a high degree, along with the clinical application of various medical imaging technologies. As an important instrument for diagnosis of brain tumor, Magnetic Resonance Imaging (MRI) has high resolving capability for parenchyma, and is without harm to human body, so MRI is the main instrument for research on brain function and pathology nowadays. As the edge contour of tumor includes abounding characteristic information of tumor pathological changes, clinicians always determine the nature of disease by analyzing the characteristic information of tumor contour. So accurate segmentation of brain tissue has important sense for diagnosis and treatment of brain tumor. The active contour model(Snake), originally presented by Kass in 1987, is an importantinstrument for medical image segmentation. The main principle of this model is that offering an initial contour with an energy function of the image to be segmented, and push the contour converging along the direction that the energy depresses, and the initial contour converges to the real contour when the energy function arrives at its minimum. The original active contour model has its intrinsic limits: First, the initial contour must, in general, be close to the real boundary; Second, poor convergence to boundary concavities. Especially it need to set initial contour near to the real boundary.This thesis first introduces the arithmetic principle of original active contour model detailedly, and improves the original model from sides of initial contour selection and definition of external force: first, considering the character of MRI image of brain tumor, adopts improved region grow algorithm for pre-segmentation to get the initial contour of active contour model. Second, use sobel gradient operator and GVF respectively for the calculating of external force of active contour model, therefore, the accuracy of ROI detection is improved. Compared with manual selection of initial contour, the method presented by this thesis can improve the efficiency, The experimental results show that the improved active contour model can get a better result for contour detection of MRI brain tumor, but for soaked tumor that with illegibility boundary, GVF-Snake can get a better result.