Ultrasound image segmentation based on Zernike moment and level set

To improve the segmentation accuracy of ultrasonic images, an ultrasonic image segmentation method based on the Zernike moments (ZMs) and the level set is presented. First, 9 ZMs with different orders and repetitions are used to extract the image features. Both the magnitudes and phases are reserved to obtain 18 feature images. Meanwhile, the weights of the feature images are calculated according to the samples obtained by sampling inside and outside of the target region of each feature image. Then, the edge indicator functions are calculated by the convolution of the feature images and the Gaussian operator. The sum of the multiplication results of the edge indicator functions and the corresponding weights of the feature images is the edge indicator function of the ultrasonic image. Finally, the ultrasonic image is segmented by the level set method based on the variation formulation. The experimental results of prostate ultrasonic images show that compared with the level set method based on the gradient and the level set method based on the ZM magnitude, the proposed method has higher segmentation accuracy, and the dice similarity coefficients are more than 95%. ©, 2015, Southeast University. All right reserved.