MRI Denoising Based on a Non-Parametric Bayesian Image Sparse Representation Method

被引：0

作者：

Chen, Xian-bo ^{[1
]}

Ding, Xing-hao ^{[1
]}

Liu, Hui ^{[1
]}

机构：

[1] Xiamen Univ, Sch Informat Sci & Technol, Xiamen 361005, Peoples R China

来源：

ADVANCED RESEARCH ON INFORMATION SCIENCE, AUTOMATION AND MATERIAL SYSTEM, PTS 1-6 | 2011年 / 219-220卷

关键词：

MRI denoising; Non-Parametric Bayesian; sparse representation; dictionary learning; spike-slab prior;

D O I：

10.4028/www.scientific.net/AMR.219-220.1354

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Magnetic Resonance images are often corrupted by Gaussian noise which highly affects the quality of MR images. In this paper, a Non-Parametric hierarchical Bayesian image sparse representation method is proposed to wipe out Gaussian distribution noise coupling in MR images. In this method a spike-slab prior is imposed on sparse coefficients, and a redundant dictionary is learned from the corrupted image. Experimental results show that the method not only improves the effect of MRI denoising, but also can obtain good estimation of the noise variance. Compared to non-local filter method, this model shows better visual quality as well as higher PSNR.

引用

页码：1354 / 1358

页数：5

共 50 条

[41] A Bayesian non-parametric method to detect clusters in Planck data
Diego, JM
Vielva, P
Martínez-González, E
Silk, J
Sanz, JL
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2002, 336 (04) : 1351 - 1363
[42] Non-parametric adaptive method for enhancing image resolution
Su, Zhigang
Zhang, Kexiang
Peng, Yingning
Wu, Renbiao
CISP 2008: FIRST INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOL 3, PROCEEDINGS, 2008, : 498 - +
[43] Bayesian Non-parametric Image Segmentation with Markov Random Field Prior
Amid, Ehsan
IMAGE ANALYSIS, SCIA 2013: 18TH SCANDINAVIAN CONFERENCE, 2013, 7944 : 76 - 84
[44] Non-parametric Bayesian models of response function in dynamic image sequences
Tichy, Ondrej
Smidl, Vaclav
COMPUTER VISION AND IMAGE UNDERSTANDING, 2016, 151 : 90 - 100
[45] Knowledge representation using non-parametric Bayesian networks for tunneling risk analysis
Wang Fan
Li Heng
Dong Chao
Ding Lieyun
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2019, 191
[46] Bayesian sparse hierarchical model for image denoising
Xiao, Jun
Zhao, Rui
Lam, Kin-Man
SIGNAL PROCESSING-IMAGE COMMUNICATION, 2021, 96
[47] Non-parametric Bayesian annotator combination
Servajean, M.
Chailan, R.
Joly, A.
INFORMATION SCIENCES, 2018, 436 : 131 - 145
[48] An unsupervised and non-parametric bayesian classifier
Zribi, M
Ghorbel, F
PATTERN RECOGNITION LETTERS, 2003, 24 (1-3) : 97 - 112
[49] An Efficient Example-based Method for CT Image Denoising based on Frequency Decomposition and Sparse Representation
Thanh-Trung Nguyen
Dinh-Hoan Trinh
Nguyen Linh-Trung
PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR COMMUNICATIONS (ATC), 2016, : 293 - 296
[50] Urine sediment cell image recognition method based on non-parametric transform
Li, Weihong
Yu, Linjie
Gong, Weiguo
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2015, 36 (12): : 2722 - 2730

← 1 2 3 4 5 →