基于归一化割的颅脑MRI肿瘤提取算法

摘要

颅脑核磁共振图像( MRI)的肿瘤图像由于自身对比度较低、肿瘤边缘模糊以及肿瘤形状复杂等因素，导致其难以被准确提取。为此，提出将归一化割算法和基于符号压力( SPF)函数的活动轮廓模型相结合，对颅脑MRI肿瘤进行提取的算法。利用基于SPF函数的活动轮廓模型，实现对归一化割算法提取肿瘤边缘的收敛，通过设置收敛的迭代次数和光滑系数完成对颅脑MRI肿瘤边缘的收敛速度和形状的控制，使最终曲线停止于真正的肿瘤边缘。仿真结果表明，该算法克服了肿瘤形状变化及对比度等因素对肿瘤提取的不利影响，能稳定而准确地提取颅脑MRI肿瘤。%It is difficult to accurately extract the brain tumor,because of the low contrast of brain Magnetic Resonance Image(MRI),the blur tumor edge and complicated brain tumor shape. Order to solve this problem,this paper puts forward the algorithm cmbcaused normalized cut with active contour model based on the slsh wessure Force ( SPF ) function to extract brain MRI tumor. It uses active contour model based on the SPF function to convergent the normalized cut extraction tumor edge,setts the convergence of the iterative number and smooth coefficient to control the MRI tumor edge convergence speed and shape, and makes the tumor edge curve to stop at the real tumor edge. Simulation results show that ths algorithm can overcome the tumor extracting negative impact of tumor shape changing and tumor contrast, and extracts the brain tumor stably and accurately.