A Fast Segmentation Algorithm of PET Images Based on Visual Saliency Model

Owing to fogged image quality and similar gray scale of PET, the current main segmentation algorithm cannot give much attention to its effects and efficiency. Therefore, this paper presents a segmentation algorithm on the basis of visual saliency model of PET images. Firstly, manual operation substituted by optimized Itti visual saliency model distinguishes PET images in a fast way. Secondly, one should preprocess the salient images acquired, and then initialize the Gaussian mixture model of foreground and background area. Finally, the PET salient images are segmented by optimized GrabCut algorithm, thus obtaining results. Compared with the other two algorithms, experimental results show that the proposed algorithm has some advantages in the simple operation, the efficient algorithm and the accurate results. At the same time, it effectively improves the efficiency of PET image segmentation and ensures the segmentation results.