说明：  ，本文提出了一种基于遗传算法的双T—Snake模型图像分割方法，它将双T—Snake模型解作为遗传算法的搜 索空间，这既继承了T—Snake模型的拓扑改变能力，又加快了遗传算法的收敛速度。由于它利用遗传算法的全局优 化性能，克服了Snake轮廓局部极小化的缺陷，从而可得到对目标的更精确的分割。将其应用于左心室MRI图像 的分割，取得了较好的效果。
(This paper presents a genetic algorithm based on dual-T-Snake model for image segmentation method, it will double T-Snake model solution as the genetic algorithm search space, which not only inherited the T-Snake model for the topology change ability, and speed up the Genetic algorithm convergence speed. Because of its global optimization using genetic algorithm performance, to overcome the local minimum of the Snake contour defects, and thus get more precise on the target partition. Will be applied to MRI image segmentation left ventricle, and achieved good results.)