扩散加权磁共振成像的变分去噪
VARIATIONAL DENOISING OF DIFFUSION WEIGHTED MRI.
作者信息
McGraw Tim, Vemuri Baba, Özarslan Evren, Chen Yunmei, Mareci Thomas
机构信息
West Virginia University, Morgantown, WV 26506, USA.
University of Florida, Gainesville, FL 32601, USA.
出版信息
Inverse Probl Imaging (Springfield). 2009 Nov;3(4):625-648. doi: 10.3934/ipi.2009.3.625.
Abstract
In this paper, we present a novel variational formulation for restoring high angular resolution diffusion imaging (HARDI) data. The restoration formulation involves smoothing signal measurements over the spherical domain and across the 3D image lattice. The regularization across the lattice is achieved using a total variation (TV) norm based scheme, while the finite element method (FEM) was employed to smooth the data on the sphere at each lattice point using first and second order smoothness constraints. Examples are presented to show the performance of the HARDI data restoration scheme and its effect on fiber direction computation on synthetic data, as well as on real data sets collected from excised rat brain and spinal cord.
摘要
在本文中，我们提出了一种用于恢复高角分辨率扩散成像（HARDI）数据的新型变分公式。该恢复公式涉及在球域和三维图像格点上对信号测量值进行平滑处理。格点上的正则化是通过基于总变差（TV）范数的方案实现的，而有限元方法（FEM）则用于在每个格点处利用一阶和二阶平滑约束对球面上的数据进行平滑处理。文中给出了示例，以展示HARDI数据恢复方案的性能及其对合成数据以及从切除的大鼠脑和脊髓收集的真实数据集上纤维方向计算的影响。
相似文献
1
VARIATIONAL DENOISING OF DIFFUSION WEIGHTED MRI.扩散加权磁共振成像的变分去噪
Inverse Probl Imaging (Springfield). 2009 Nov;3(4):625-648. doi: 10.3934/ipi.2009.3.625.
2
HARDI denoising: variational regularization of the spherical apparent diffusion coefficient sADC.高角分辨率扩散成像去噪：球形表观扩散系数sADC的变分正则化
Inf Process Med Imaging. 2009;21:515-27. doi: 10.1007/978-3-642-02498-6_43.
3
A VARIATIONAL MODEL FOR DENOISING HIGH ANGULAR RESOLUTION DIFFUSION IMAGING.一种用于高角分辨率扩散成像去噪的变分模型。
Proc IEEE Int Symp Biomed Imaging. 2012:530-533. doi: 10.1109/ISBI.2012.6235602.
4
HARDI DATA DENOISING USING VECTORIAL TOTAL VARIATION AND LOGARITHMIC BARRIER.基于矢量全变差和对数障碍的硬数据去噪
Inverse Probl Imaging (Springfield). 2010 May 1;4(2):273-310. doi: 10.3934/ipi.2010.4.273.
5
Modeling diffusion-weighted MRI as a spatially variant gaussian mixture: application to image denoising.将扩散加权磁共振成像建模为空间变化的高斯混合体：在图像去噪中的应用。
Med Phys. 2011 Jul;38(7):4350-64. doi: 10.1118/1.3599724.
6
Denoising high angular resolution diffusion imaging data by combining singular value decomposition and non-local means filter.通过结合奇异值分解和非局部均值滤波器来对高角度分辨率扩散成像数据进行去噪。
J Neurosci Methods. 2019 Jan 15;312:105-113. doi: 10.1016/j.jneumeth.2018.11.020. Epub 2018 Nov 22.
7
FAST DISPLACEMENT PROBABILITY PROFILE APPROXIMATION FROM HARDI USING 4TH-ORDER TENSORS.使用四阶张量从扩散张量成像中进行快速位移概率分布近似
Proc IEEE Int Symp Biomed Imaging. 2008 May 14;5:911-914. doi: 10.1109/ISBI.2008.4541145.
8
A localized Richardson-Lucy algorithm for fiber orientation estimation in high angular resolution diffusion imaging.一种用于高角分辨率扩散成像中纤维方向估计的局部理查森- Lucy算法。
Med Phys. 2015 May;42(5):2524-39. doi: 10.1118/1.4917082.
9
Q-ball imaging models: comparison between high and low angular resolution diffusion-weighted MRI protocols for investigation of brain white matter integrity.Q球成像模型：用于研究脑白质完整性的高、低角分辨率扩散加权磁共振成像协议之间的比较
Neuroradiology. 2016 Feb;58(2):209-15. doi: 10.1007/s00234-015-1616-3. Epub 2015 Nov 16.
10
lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain.低场扩散加权成像：一种在梯度方向域中对扩散加权图像进行预处理的新方案。
Front Neurol. 2015 Jan 12;5:290. doi: 10.3389/fneur.2014.00290. eCollection 2014.
引用本文的文献
1
Robust frequency-dependent diffusional kurtosis computation using an efficient direction scheme, axisymmetric modelling, and spatial regularization.使用高效方向方案、轴对称建模和空间正则化进行稳健的频率依赖性扩散峰度计算。
Imaging Neurosci (Camb). 2024 Jan 5;2. doi: 10.1162/imag_a_00055. eCollection 2024.
2
Denoising for Improved Parametric MRI of the Kidney: Protocol for Nonlocal Means Filtering.用于改善肾脏参数 MRI 的去噪：非局部均值滤波的协议。
Methods Mol Biol. 2021;2216:565-576. doi: 10.1007/978-1-0716-0978-1_34.
3
Smoothing fields of weighted collections with applications to diffusion MRI processing.加权集合的平滑场及其在扩散磁共振成像处理中的应用。
Proc SPIE Int Soc Opt Eng. 2014 Mar 21;9034:90342D. doi: 10.1117/12.2043959.
4
Diffusion weighted image denoising using overcomplete local PCA.基于过完备局部主成分分析的弥散加权图像去噪。
PLoS One. 2013 Sep 3;8(9):e73021. doi: 10.1371/journal.pone.0073021. eCollection 2013.
5
Denoising diffusion-weighted magnitude MR images using rank and edge constraints.使用秩和边缘约束去噪扩散加权幅度磁共振图像。
Magn Reson Med. 2014 Mar;71(3):1272-84. doi: 10.1002/mrm.24728.
6
A VARIATIONAL MODEL FOR DENOISING HIGH ANGULAR RESOLUTION DIFFUSION IMAGING.一种用于高角分辨率扩散成像去噪的变分模型。
Proc IEEE Int Symp Biomed Imaging. 2012:530-533. doi: 10.1109/ISBI.2012.6235602.
7
Improved diffusion imaging through SNR-enhancing joint reconstruction.通过 SNR 增强的联合重建提高弥散成像质量。
Magn Reson Med. 2013 Jan;69(1):277-89. doi: 10.1002/mrm.24229. Epub 2012 Mar 5.
8
Modeling diffusion-weighted MRI as a spatially variant gaussian mixture: application to image denoising.将扩散加权磁共振成像建模为空间变化的高斯混合体：在图像去噪中的应用。
Med Phys. 2011 Jul;38(7):4350-64. doi: 10.1118/1.3599724.
9
HARDI DATA DENOISING USING VECTORIAL TOTAL VARIATION AND LOGARITHMIC BARRIER.基于矢量全变差和对数障碍的硬数据去噪
Inverse Probl Imaging (Springfield). 2010 May 1;4(2):273-310. doi: 10.3934/ipi.2010.4.273.
本文引用的文献
1
Image analysis using multigrid relaxation methods.使用多重网格松弛方法进行图像分析。
IEEE Trans Pattern Anal Mach Intell. 1986 Feb;8(2):129-39. doi: 10.1109/tpami.1986.4767767.
2
Rician noise removal by non-Local Means filtering for low signal-to-noise ratio MRI: applications to DT-MRI.基于非局部均值滤波的低信噪比磁共振成像莱斯噪声去除：在扩散张量磁共振成像中的应用
Med Image Comput Comput Assist Interv. 2008;11(Pt 2):171-9. doi: 10.1007/978-3-540-85990-1_21.
3
Impact of Rician adapted Non-Local Means filtering on HARDI.莱斯适应非局部均值滤波对高分辨率扩散成像的影响。
Med Image Comput Comput Assist Interv. 2008;11(Pt 2):122-30. doi: 10.1007/978-3-540-85990-1_15.
4
Efficient computation of PDF-based characteristics from diffusion MR signal.基于扩散磁共振信号高效计算基于概率密度函数的特征
Med Image Comput Comput Assist Interv. 2008;11(Pt 2):70-8. doi: 10.1007/978-3-540-85990-1_9.
5
Noise correction on Rician distributed data for fibre orientation estimators.用于纤维取向估计器的莱斯分布数据的噪声校正
IEEE Trans Med Imaging. 2008 Sep;27(9):1242-51. doi: 10.1109/TMI.2008.920615.
6
Color TV: total variation methods for restoration of vector-valued images.彩色电视：用于矢量值图像恢复的全变差方法。
IEEE Trans Image Process. 1998;7(3):304-9. doi: 10.1109/83.661180.
7
Non-local means variants for denoising of diffusion-weighted and diffusion tensor MRI.用于扩散加权磁共振成像和扩散张量磁共振成像去噪的非局部均值变体
Med Image Comput Comput Assist Interv. 2007;10(Pt 2):344-51. doi: 10.1007/978-3-540-75759-7_42.
8
Clinical DT-MRI estimation, smoothing, and fiber tracking with log-Euclidean metrics.基于对数欧几里得度量的临床扩散张量磁共振成像估计、平滑处理及纤维追踪
IEEE Trans Med Imaging. 2007 Nov;26(11):1472-82. doi: 10.1109/TMI.2007.899173.
9
Bilateral filtering of diffusion tensor magnetic resonance images.扩散张量磁共振图像的双边滤波
IEEE Trans Image Process. 2007 Oct;16(10):2463-75. doi: 10.1109/tip.2007.904964.
10
Feature-preserving MRI denoising: a nonparametric empirical Bayes approach.保留特征的磁共振成像去噪：一种非参数经验贝叶斯方法。
IEEE Trans Med Imaging. 2007 Sep;26(9):1242-55. doi: 10.1109/TMI.2007.900319.
Zotero 插件