Abstract：Objective To suppress the noise and improve the quality of brain CT image by the method based on a combination of
non-local mean filtering and wavelet. Methods Experiments were conducted on simulation data to estimate the filtering parameters
under different noise levels and the brain CT image from human subjects to demonstrate the validity of the proposed theory. The
effect was compared with the traditional non-local mean filtering. Finally, the peak signal to noise ratio (PSNR) of the image before
and after filtering was statistically analyzed by paired t test. Results This method can increase the PSNR of the CT image with white
noise by 5~10 dB, which was 3~5 dB higher than the traditional non-local mean filtered image. The PSNR of the image before and
after filtering was statistically different (P＜0.001). Conclusion The method based on a combination of non-local mean filtering
and wavelet can process the brain CT images with different noise levels adaptively, effectively suppress noise, improve PSBR, while
retaining image details and edges, and improving image quality.
张爱桃，陈小茜，肖雨，郭东敏，周旭，李连捷. 自适应非局部均值滤波与小波相结合的脑部CT去噪研究[J]. 中国医疗设备, 2021, 36(12): 73-77.
ZHANG Aitao, CHEN Xiaoxi, XIAO Yu, GUO Dongmin, ZHOU Xu, LI Lianjie. Denoising Research of Brain CT Based on Adaptive Non-Local Mean Filtering and Wavelet. China Medical Devices, 2021, 36(12): 73-77.
