Denoising Low-Dose CT Images Using Multiframe Blind Source Separation and Block Matching Filter

In order to reduce radiation effect during CT scans, low-dose techniques are employed in different medical imaging applications. But images in the low-dose CT tend to be rather noisy to be diagnostically useful. One way to improve the quality of low-dose CT images is to use a multiframe imaging technique. Here, we proposed a blind source separation (BSS) based CT image method using a multiframe low-dose image sequence. Because we found that BSS alone cannot denoise the image completely, we incorporated a nonlocal GroupWise block matching 3-D filter with BSS using the noise statistics, extracted from the noise components. With this technique, we produced a better quality image than that produced with a single frame half dose CT image and other multiframe imaging techniques, such as, frame averaging and applying the Wiener filter after BSS. Denoising performance, spatial resolution, and noise characteristics were measured by evaluating the peak signal to noise ratio, structural similarity index, modulation transfer function, and Bland–Altman analysis. This hybrid model shows a better denoising performance with less compromise in image details as more frames are included in an image sequence.