图像分割是由图像处理到图像分析的关键步骤，涉及到计算机视觉技术的复杂问题。在医学图像方面，许多应用大都依赖于对图像中目标轮廓的准确提取。基于微分算子检测的方法几乎都对噪声较为敏感且不能保证得到连续的边缘，无法用于辨识和分析目标。由Kass提出的基于主动轮廓线的Snake模型[1]，用一个具有一定弹性的封闭曲线，在曲线自身形状约束力和由图像数据计算而来的外部力的共同作用下演化，来逼近目标边界，完成对图像的分割。

GVF snake VC++做的-Image segmentation by image processing to image analysis of the key steps involved in computer vision technology to complex problems. In medical images, many applications largely depends on the target images extracted contour accuracy. Based on the differential operator method of detecting almost all more sensitive to noise and can not guarantee that they will get straight edge, can not be used for target identification and analysis. Kass raised by the active contour based on the Snake model [1], with a certain flexibility of the closed curve in the curve shape their own binding and calculated by the image data from the external force under the joint effect of the evolution of the boundary to approximate the target , completion of the image segmentation. GVF snake VC++ Make the