title: Evaluation of non-local means based denoising filters for diffusion kurtosis imaging using a new phantom.
abstract: 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 human brain, and the pipeline used to construct the phantom consists of diffusion-weighted (DW) image filtering, diffusion and kurtosis tensor regularization, and DW image reconstruction. The phantom preserves the image structure while minimizing image noise, and thus can be used as ground truth in the evaluation. Second, we used the phantom to evaluate three representative algorithms of non-local means (NLM). Results showed that one scheme of vector-based NLM, which uses DWI data with redundant information acquired at different b-values, produced the most reliable estimation of DKI parameters in terms of Mean Square Error (MSE), Bias and standard deviation (Std). The result of the comparison based on the phantom was consistent with those based on real datasets.
authors: Shanghai Key Laboratory of Magnetic Resonance, Physics Department, East China Normal University, Shanghai, China; Shanghai Medical Instrumentation College, University of Shanghai for Science and Technology, Shanghai, China.
authors: Min-Xiong
authors: MX
authors: Zhou
authors: MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China.
authors: Xu
authors: X
authors: Yan
authors: Shanghai Key Laboratory of Magnetic Resonance, Physics Department, East China Normal University, Shanghai, China.
authors: Hai-Bin
authors: HB
authors: Xie
authors: Shanghai Key Laboratory of Magnetic Resonance, Physics Department, East China Normal University, Shanghai, China.
authors: Hui
authors: H
authors: Zheng
authors: Key Laboratory of Brain Functional Genomics, Institute of Cognitive Neuroscience, East China Normal University, Shanghai, China; MRI Unit, and Epidemiology Division, Columbia University Department of Psychiatry, and New York State Psychiatric Institute, NYSPI Unit 24, 1051 Riverside Drive, New York, New York, 10032, United States of America.
authors: Dongrong
authors: D
authors: Xu
authors: Shanghai Key Laboratory of Magnetic Resonance, Physics Department, East China Normal University, Shanghai, China.
authors: Guang
authors: G
authors: Yang
mesh_terms: D000465:Algorithms; D038524:Diffusion Magnetic Resonance Imaging / Q000295:instrumentation*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D019047:Phantoms, Imaging; D011336:Probability; D059629:Signal-To-Noise Ratio
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