Zengliang F, Xiaojun C, Ming Y, Chengtao W
Institute of Life Quality via Mechanical Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Dongchuan Road 800, Shanghai, PR China.
J Med Eng Technol. 2009;33(4):303-8. doi: 10.1080/03091900802454426.
A novel method for the segmentation of serial images is proposed. In the presented framework, the driving force acts as the attracting term to propel the evolving curve towards the object boundaries, and the adaptive term changes the sign of driving force accordingly. Therefore, the evolving curves can arrive at the desired direction without a requirement for the initial curve to be strictly inside or outside the object. A weighted length term is used to keep the smoothness of curve and penalize the formulation of discontinuities. To prevent the level set function deviating from a signed distance function, a distance rectifying flow is also added to the model; therefore the time-consuming re-initialization procedure is completely avoided. Experiments on both synthetic image and CT serial images demonstrate the feasibility and efficiency of the method.
提出了一种用于序列图像分割的新方法。在所提出的框架中，驱动力作为吸引项，推动演化曲线朝着物体边界移动，而自适应项相应地改变驱动力的符号。因此，演化曲线能够到达期望的方向，而无需初始曲线严格位于物体内部或外部。使用加权长度项来保持曲线的平滑性并惩罚不连续性的形成。为防止水平集函数偏离符号距离函数，模型中还添加了距离校正流；因此完全避免了耗时的重新初始化过程。在合成图像和CT序列图像上的实验证明了该方法的可行性和有效性。
