多尺度几何活动曲线及MR图像边界提取

活动曲线方法是８０年代末发展起来的基于模型的图像分割方法，主要有两大类，能量活动曲线方法和几何活动曲线方法，几何活动曲线言方法在数学上比较完备，较好地克服了能量的许多缺点，但是在医学图像分割中，尤其是结构性噪声比较严重的情况下，几何活动曲线向边界的演化会受到一定程度的影响，为了解决这个问题，作者利用基于小波变换的多尺度边缘检测算法，提出了多尺度几何活动曲线模型，在人体头部ＭＲ图像脑边界的提取中，多

Multiscale Geometric Active Contour Model and Boundary Extraction in MR Images

Active contour methods are model based approaches for image segmentation and were developed in the late 1980s.There are two main categories of these methods:energy based methods and geometric methods.Geometric method are intrinsic models.Because of its completeness in mathematics,geometric active contour model overcomes many difficulties of the energy bases active contour model.However,in medical images with heavy structural noise,the evolution of the geometric active contour will be seriously affected. To handle this problem,this paper proposes a multiscale geometric active contour model,based upon the multiscale edge detection algorithm.In the human brain MR images, the proposed multiscale geometric active contour model successfully extracts the complex brain contour,regardless of the heavy structural noise between gray matter and white matter.