Evaluation of Non-Local Means Based Denoising Filters for Diffusion Kurtosis Imaging Using a New Phantom
نویسندگان
چکیده
منابع مشابه
Evaluation of Non-Local Means Based Denoising Filters for Diffusion Kurtosis Imaging Using a New Phantom
Image denoising has a profound impact on the precision of estimated parameters in diffusion kurtosis imaging (DKI). This work first proposes an approach to constructing a DKI phantom that can be used to evaluate the performance of denoising algorithms in regard to their abilities of improving the reliability of DKI parameter estimation. The phantom was constructed from a real DKI dataset of a h...
متن کاملSpectral denoising for MR Spectroscopic Imaging using Non-Local Means
Purpose Magnetic resonance spectroscopic imaging (MRSI) is an imaging modality used for studying tissues in-vivo in order to assess and quantify metabolites for diagnostic purposes. However, long scanning times, low spatial resolution, poor signal-to-noise ratio (SNR) and the subsequent noise-sensitive non-linear model fitting are major roadblocks in accurately quantifying the metabolite concen...
متن کاملNon-Local Means Denoising
We present in this paper a new denoising method called non-local means. The method is based on a simple principle: replacing the color of a pixel with an average of the colors of similar pixels. But the most similar pixels to a given pixel have no reason to be close at all. It is therefore licit to scan a vast portion of the image in search of all the pixels that really resemble the pixel one w...
متن کاملNon-local Means for Stereo Image Denoising Using Structural Similarity
We present a novel stereo image denoising algorithm. Our algorithm takes as an input a pair of noisy images of an object captured form two different directions. We use the structural similarity index as a similarity metric for identifying locations of similar patches in the input images. We adapt the Non-Local Means algorithm for denoising collected patches from the input images. We validate ou...
متن کاملNon-Local Means Variants for Denoising of Diffusion-Weighted and Diffusion Tensor MRI
Diffusion tensor imaging (DT-MRI) is very sensitive to corrupting noise due to the non linear relationship between the diffusion-weighted image intensities (DW-MRI) and the resulting diffusion tensor. Denoising is a crucial step to increase the quality of the estimated tensor field. This enhanced quality allows for a better quantification and a better image interpretation. The methods proposed ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLOS ONE
سال: 2015
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0116986