CT Image Segmentation Method Combining Wavelet Transform and RSF Model

To solve the problems of artifacts and weak edges of industrial computed tomography (CT) images, an image region-scalable fitting energy minimization segmentation method based on wavelet transform is proposed to achieve the accurate positioning of image edges, and improve the image measurement accuracy. First, the wavelet transform is used to preprocess the image in order to reduce metal artifacts. Then, the proposed method is employed to accurately segment the image, which aims to improve the location accuracy of the edge of the region of interest. Actual data measurement results show that the proposed method can effectively reduce the effect on weak edges of the images, and the relative error of measurement is less than 0.7%, which is 1.4 times higher than that of the Chan-Vese algorithm and meets the requirements of measurement applications.