基于稀疏正则化从简化的高分辨率扩散成像数据中进行概率取向分布函数估计
Probabilistic ODF estimation from reduced HARDI data with sparse regularization.
作者信息
Tristán-Vega Antonio, Westin Carl-Fredrik
机构信息
Laboratory of Mathematics in Imaging, Brigham and Women's Hospital, Boston, USA.
出版信息
Med Image Comput Comput Assist Interv. 2011;14(Pt 2):182-90. doi: 10.1007/978-3-642-23629-7_23.
Abstract
High Angular Resolution Diffusion Imaging (HARDI) demands a higher amount of data measurements compared to Diffusion Tensor Imaging (DTI), restricting its use in practice. We propose to represent the probabilistic Orientation Distribution Function (ODF) in the frame of Spherical Wavelets (SW), where it is highly sparse. From a reduced subset of measurements (nearly four times less than the standard for HARDI), we pose the estimation as an inverse problem with sparsity regularization. This allows the fast computation of a positive, unit-mass, probabilistic ODF from 14-16 samples, as we show with both synthetic diffusion signals and real HARDI data with typical parameters.
摘要
与扩散张量成像（DTI）相比，高角分辨率扩散成像（HARDI）需要更多的数据测量，这限制了它在实际中的应用。我们建议在球面小波（SW）框架中表示概率性取向分布函数（ODF），在该框架中它是高度稀疏的。从减少的测量子集中（比HARDI标准少近四倍），我们将估计问题构建为一个具有稀疏正则化的逆问题。这使得我们能够从14 - 16个样本中快速计算出一个正的、单位质量的概率性ODF，我们在合成扩散信号和具有典型参数的真实HARDI数据中都证明了这一点。
相似文献
1
Probabilistic ODF estimation from reduced HARDI data with sparse regularization.基于稀疏正则化从简化的高分辨率扩散成像数据中进行概率取向分布函数估计
Med Image Comput Comput Assist Interv. 2011;14(Pt 2):182-90. doi: 10.1007/978-3-642-23629-7_23.
2
Deterministic and probabilistic tractography based on complex fibre orientation distributions.基于复杂纤维取向分布的确定性和概率性纤维束成像。
IEEE Trans Med Imaging. 2009 Feb;28(2):269-86. doi: 10.1109/TMI.2008.2004424.
3
Tractometer: towards validation of tractography pipelines.束径仪：用于追踪技术管道的验证。
Med Image Anal. 2013 Oct;17(7):844-57. doi: 10.1016/j.media.2013.03.009. Epub 2013 Apr 25.
4
Diffeomorphism invariant Riemannian framework for ensemble average propagator computing.用于系综平均传播子计算的微分同胚不变黎曼框架。
Med Image Comput Comput Assist Interv. 2011;14(Pt 2):98-106. doi: 10.1007/978-3-642-23629-7_13.
5
How does B-value affect HARDI reconstruction using clinical diffusion MRI data?B值如何影响使用临床扩散磁共振成像数据进行的高分辨率扩散成像重建？
PLoS One. 2015 Mar 24;10(3):e0120773. doi: 10.1371/journal.pone.0120773. eCollection 2015.
6
Estimation of the CSA-ODF using Bayesian compressed sensing of multi-shell HARDI.利用多壳高分辨率扩散成像的贝叶斯压缩感知估计CSA-ODF
Magn Reson Med. 2014 Nov;72(5):1471-85. doi: 10.1002/mrm.25046. Epub 2013 Dec 12.
7
Model-free, regularized, fast, and robust analytical orientation distribution function estimation.无模型、正则化、快速且稳健的解析取向分布函数估计
Med Image Comput Comput Assist Interv. 2010;13(Pt 1):648-56. doi: 10.1007/978-3-642-15705-9_79.
8
Segmenting thalamic nuclei: what can we gain from HARdI?分割丘脑核团：我们能从高角分辨率扩散成像中获得什么？
Med Image Comput Comput Assist Interv. 2011;14(Pt 2):141-8. doi: 10.1007/978-3-642-23629-7_18.
9
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.
10
Detection of crossing white matter fibers with high-order tensors and rank-k decompositions.利用高阶张量和秩-k分解检测交叉白质纤维
Inf Process Med Imaging. 2011;22:538-49. doi: 10.1007/978-3-642-22092-0_44.
引用本文的文献
1
A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging.压缩感知扩散谱成像衍生测量的实际评估。
Hum Brain Mapp. 2024 Apr;45(5):e26580. doi: 10.1002/hbm.26580.
2
Establishing the Validity of Compressed Sensing Diffusion Spectrum Imaging.确定压缩感知扩散频谱成像的有效性。
bioRxiv. 2023 Feb 23:2023.02.22.529546. doi: 10.1101/2023.02.22.529546.
3
Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors.基于kq空间采样和解剖学先验知识的扩散磁共振成像中快速纤维方向估计
J Imaging. 2021 Oct 27;7(11):226. doi: 10.3390/jimaging7110226.
4
Histologically derived fiber response functions for diffusion MRI vary across white matter fibers-An ex vivo validation study in the squirrel monkey brain.组织学衍生的弥散磁共振纤维响应函数在白质纤维中存在差异——在松鼠猴脑中的一项离体验证研究。
NMR Biomed. 2019 Jun;32(6):e4090. doi: 10.1002/nbm.4090. Epub 2019 Mar 25.
5
Quantitative evaluation of fiber tractography with a Delaunay triangulation-based interpolation approach.基于 Delaunay 三角剖分的插值方法对纤维束追踪的定量评估。
Med Biol Eng Comput. 2019 Apr;57(4):925-938. doi: 10.1007/s11517-018-1932-y. Epub 2018 Nov 28.
6
A Sparse Bayesian Learning Algorithm for White Matter Parameter Estimation from Compressed Multi-shell Diffusion MRI.一种用于从压缩多壳扩散磁共振成像估计白质参数的稀疏贝叶斯学习算法。
Med Image Comput Comput Assist Interv. 2017 Sep;10433:602-610. doi: 10.1007/978-3-319-66182-7_69. Epub 2017 Sep 4.
7
Estimation of white matter fiber parameters from compressed multiresolution diffusion MRI using sparse Bayesian learning.基于稀疏贝叶斯学习的压缩多分辨率扩散 MRI 中白质纤维参数估计。
Neuroimage. 2018 Feb 15;167:488-503. doi: 10.1016/j.neuroimage.2017.06.052. Epub 2017 Jun 29.
8
Multi-shell diffusion signal recovery from sparse measurements.从稀疏测量中恢复多壳扩散信号
Med Image Anal. 2014 Oct;18(7):1143-56. doi: 10.1016/j.media.2014.06.003. Epub 2014 Jul 5.
9
Estimation of the CSA-ODF using Bayesian compressed sensing of multi-shell HARDI.利用多壳高分辨率扩散成像的贝叶斯压缩感知估计CSA-ODF
Magn Reson Med. 2014 Nov;72(5):1471-85. doi: 10.1002/mrm.25046. Epub 2013 Dec 12.
10
Fast dictionary-based reconstruction for diffusion spectrum imaging.基于字典的快速扩散谱成像重建。
IEEE Trans Med Imaging. 2013 Nov;32(11):2022-33. doi: 10.1109/TMI.2013.2271707. Epub 2013 Jul 4.
本文引用的文献
1
Recent advances in diffusion MRI modeling: Angular and radial reconstruction.扩散磁共振成像建模的新进展：角向和径向重建。
Med Image Anal. 2011 Aug;15(4):369-96. doi: 10.1016/j.media.2011.02.002. Epub 2011 Feb 16.
2
Fast and accurate reconstruction of HARDI data using compressed sensing.使用压缩感知技术对高分辨率扩散成像（HARDI）数据进行快速准确的重建。
Med Image Comput Comput Assist Interv. 2010;13(Pt 1):607-14. doi: 10.1007/978-3-642-15705-9_74.
3
A new methodology for the estimation of fiber populations in the white matter of the brain with the Funk-Radon transform.一种利用 Funk-Radon 变换估计脑白质中纤维群体的新方法。
Neuroimage. 2010 Jan 15;49(2):1301-15. doi: 10.1016/j.neuroimage.2009.09.070. Epub 2009 Oct 6.
4
Multi-fiber reconstruction from diffusion MRI using mixture of Wisharts and sparse deconvolution.基于威沙特混合模型和稀疏反卷积的扩散磁共振成像多纤维重建
Inf Process Med Imaging. 2007;20:384-95. doi: 10.1007/978-3-540-73273-0_32.
5
Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging.利用扩散谱磁共振成像绘制复杂组织结构图。
Magn Reson Med. 2005 Dec;54(6):1377-86. doi: 10.1002/mrm.20642.
6
Q-ball imaging.Q球成像
Magn Reson Med. 2004 Dec;52(6):1358-72. doi: 10.1002/mrm.20279.
Zotero 插件