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 1 radiologist)—using real DCE-MRI data. The results of the evaluation provide evidence, at the α=0.05 level of significance, that both groups of observers deem the DNLM algorithm to perform visually better than all of the other algorithms.