In order to solve the problem of many noises and low spatial resolution of low-dose CT images, a low-dose CT image denoising method based on improved dual-tree complex wavelet transform and guided filtering is proposed. Firstly, the low-dose CT image is decomposed by DTCWT, the high-frequency subband coefficients are denoised by goodness-of-fit test framework, the low-frequency subband is denoised by trilateral filtering, and the initial denoised image is obtained by inverse DTCWT reconstruction. Then, the low-frequency subband image which is denoised and interpolated is used as the guide image to guide and filter the CT image. Then, the detail residual image is generated by combining the denoising results of the initial denoising image and the guide filter. Finally, the BM3D threshold algorithm is used to Denoise the remaining details of the image twice, and the final denoised image is obtained by superimposing the denoising results twice. The experimental results show that this method is better than other traditional image denoising algorithms, and the edge outline and texture features of the image are well preserved while suppressing noise, and has a remarkable denoising effect on low-dose CT images.