Medical image segmentation based on Maximum Entropy Multi-Threshold Segmentation by Improved Cuckoo Search Algorithm

In order to improve the effect of medical image segmentation,this paper proposes a novel medical image segmentation method based on maximum entropy multi- threshold segmentation optimized by improved cuckoo search algorithm. Firstly,threshold optimization objective function of maximum entropy method is obtained,and then improved cuckoo search algorithm is used to solve the objective function and find the optimal segmentation threshold of the medical image. Finally,medical image is segmented according to the optimal threshold,and the performance is tested by simulation. The results show that the proposed method can improve the accuracy of medical image segmentation and has good robustness.