Improved fast medical image segmentation method
一种改进的快速医学图像分割方法*

In order to determine the best histogram entropy of medical image, this paper proposed a fast segmentation method based on improved evolutionary algorithm which could adjust the crossover and mutation possibility adaptively. It ensured the population diversity and overcame the local optimal and fast convergence of traditional evolutionary algorithm. The best thre shold searched was not only more stability but also greatly reduced searching time, and rapidly implemented medical image segmentation, moreover, the image after segmentation had a strong readability. Experimental results show that the method is faster and has a better segmentation effect.