An Application of Non-local Means Algorithm for Denoising Low Dose Computed Tomography

Abstract

To minimize the radiation risk in clinical examination using X-ray CT, low dose CT imaging is desirable in clinical practice. Lowering radiation dose degrades the reconstructed image quality and decreases the diagnostic performance of the image. Hence image denoising and signal enhancement in low dose CT imaging is one of the foremost challenging issue. The NLM algorithm has been successfully applied in removing noise and artefacts from corrupted natural images. This paper studies the application of non-local means (NLM) algorithm in removing noise from low dose CT lung images. In this study low dose CT images are denoised by applying NLM filer in two different ways. In the first application NLM filter is used to remove noise from projection data before reconstructing the images. In the second method images are denoised by applying NLM in the image domain after reconstruction. The Performances of both image space and projection space denoising is compared and evaluated quantitatively using PSNR and SSIM. Results shows that NLM filter can successfully applied to denoise low dose CT images and better results can obtained if the filter is applied on reconstructed images.