MRI denoising by NeighShrink based on chi-square unbiased risk estimation

作者：

Highlights：

• We first developed an unnormalized and undecimated Haar wavelet domain CURE estimation for NeighShrink for MR images denoising.

• We propose our method—NeighShrinkCURE+ BF/CS=9 by combing NeighShrinkCURE, a fast bilateral filter with fast cycle-spin technology.

• Both quantitatively and qualitatively, overall performance of the proposed algorithm is better than that of some existing similar algorithms.

摘要

•We first developed an unnormalized and undecimated Haar wavelet domain CURE estimation for NeighShrink for MR images denoising.•We propose our method—NeighShrinkCURE+ BF/CS=9 by combing NeighShrinkCURE, a fast bilateral filter with fast cycle-spin technology.•Both quantitatively and qualitatively, overall performance of the proposed algorithm is better than that of some existing similar algorithms.

论文关键词：NeighShrinkCURE,MRI denoising,Wavelet transform,Bilateral filter,Cycle spinning

论文评审过程：Received 23 June 2017, Revised 27 November 2018, Accepted 4 December 2018, Available online 1 February 2019, Version of Record 13 June 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2018.12.001