Medical image segmentation based on maximum entropy multi-threshold segmentation optimized by improved cuckoo search algorithm

In order to improve the accuracy of medical image segmentation and overcome the shortcomings of maximum entropy segmentation algorithm, the paper proposes the medical image segmentation based on maximum entropy multi-threshold segmentation optimized by improved cuckoo search algorithm (MCS). Firstly, the maximum entropy method is adopted to find the optimization objective function, then the improved cuckoo search algorithm is used to optimize the objective function, find the best segmentation threshold of the medical image, and achieve medical image segmentation; finally, simulation tests are carried out for a variety of images. The results indicate that the method proposed by the paper can improve the accuracy of medical image segmentation, and have good robustness and good practical value.