A New Denoising Method for Dynamic Contrast-Enhanced MRI

This paper presents a new algorithm for denoising dynamic contrast-enhanced (DCE) MR images. The algorithm is called Dynamic Non-Local Means and is a novel variation on the Non-Local Means (NL-Means) algorithm. It exploits the redundancy of information in the DCE-MRI sequence of images. An evaluation of the performance of the algorithm relative to six other denoising algorithms-Gaussian filtering, the original NL-Means algorithm, bilateral filtering, anisotropic diffusion filtering, the wavelets adaptive multiscale products threshold method, and the traditional wavelet thresholding method-is also presented. The evaluation was performed by two groups of expert observers-18 signal/image processing experts, and 9 clinicians (8 radiographers and I radiologist)-using real DCE-MRI data. The results of the evaluation provide evidence, at the alpha=0.05 level of significance, that both groups of observers deem the DNLM algorithm to perform visually better than all of the other algorithms.