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通过统一的多壳HARDI重建进行非负定EAP和ODF估计。

Nonnegative definite EAP and ODF estimation via a unified multi-shell HARDI reconstruction.

作者信息

Cheng Jian, Jiang Tianzi, Deriche Rachid

机构信息

CCM, LIAMA, Institute of Automation, Chinese Academy of Sciences, China.

出版信息

Med Image Comput Comput Assist Interv. 2012;15(Pt 2):313-21. doi: 10.1007/978-3-642-33418-4_39.

DOI:10.1007/978-3-642-33418-4_39
PMID:23286063
Abstract

In High Angular Resolution Diffusion Imaging (HARDI), Orientation Distribution Function (ODF) and Ensemble Average Propagator (EAP) are two important Probability Density Functions (PDFs) which reflect the water diffusion and fiber orientations. Spherical Polar Fourier Imaging (SPFI) is a recent model-free multi-shell HARDI method which estimates both EAP and ODF from the diffusion signals with multiple b values. As physical PDFs, ODFs and EAPs are nonnegative definite respectively in their domains S2 and R3. However, existing ODF/EAP estimation methods like SPFI seldom consider this natural constraint. Although some works considered the nonnegative constraint on the given discrete samples of ODF/EAP, the estimated ODF/EAP is not guaranteed to be nonnegative definite in the whole continuous domain. The Riemannian framework for ODFs and EAPs has been proposed via the square root parameterization based on pre-estimated ODFs and EAPs by other methods like SPFI. However, there is no work on how to estimate the square root of ODF/EAP called as the wavefuntion directly from diffusion signals. In this paper, based on the Riemannian framework for ODFs/EAPs and Spherical Polar Fourier (SPF) basis representation, we propose a unified model-free multi-shell HARDI method, named as Square Root Parameterized Estimation (SRPE), to simultaneously estimate both the wavefunction of EAPs and the nonnegative definite ODFs and EAPs from diffusion signals. The experiments on synthetic data and real data showed SRPE is more robust to noise and has better EAP reconstruction than SPFI, especially for EAP profiles at large radius.

摘要

在高角分辨率扩散成像(HARDI)中,方向分布函数(ODF)和总体平均传播子(EAP)是两个重要的概率密度函数(PDF),它们反映了水的扩散和纤维方向。球面极坐标傅里叶成像(SPFI)是一种最新的无模型多壳层HARDI方法,它能从具有多个b值的扩散信号中估计EAP和ODF。作为物理PDF,ODF和EAP在其定义域S2和R3中分别是非负定的。然而,现有的ODF/EAP估计方法,如SPFI,很少考虑这种自然约束。虽然一些工作考虑了对给定离散样本的ODF/EAP的非负约束,但估计出的ODF/EAP在整个连续域中并不能保证是非负定的。通过基于其他方法(如SPFI)预先估计的ODF和EAP的平方根参数化,已经提出了ODF和EAP的黎曼框架。然而,关于如何直接从扩散信号中估计被称为波函数的ODF/EAP的平方根,尚无相关工作。在本文中,基于ODF/EAP的黎曼框架和球面极坐标傅里叶(SPF)基表示,我们提出了一种统一的无模型多壳层HARDI方法,称为平方根参数化估计(SRPE),以同时从扩散信号中估计EAP的波函数以及非负定的ODF和EAP。在合成数据和真实数据上的实验表明,SRPE对噪声更具鲁棒性,并且比SPFI具有更好的EAP重建效果,特别是对于大半径处的EAP轮廓。

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