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    • 1. 发明授权
    • System, method and computer accessible medium for providing real-time diffusional kurtosis imaging and for facilitating estimation of tensors and tensor-derived measures in diffusional kurtosis imaging
    • 系统,方法和计算机可访问介质,用于提供实时扩散峰度成像,并有助于估计扩张峰度成像中的张量和张量推导测量
    • US08811706B2
    • 2014-08-19
    • US13022488
    • 2011-02-07
    • Jens JensenJoseph HelpernAli TabeshEls Fieremans
    • Jens JensenJoseph HelpernAli TabeshEls Fieremans
    • G06T7/00A61B5/055
    • G01R33/56341
    • Exemplary method, system, and computer-accessible medium can be provided for determining a measure of diffusional kurtosis by receiving data relating to at least one diffusion weighted image, and determining a measure of a diffusional kurtosis as a function of the received data using a closed form solution procedure. In accordance with certain exemplary embodiments of the present disclosure, provided herein are computer-accessible medium, systems and methods for, e.g., imaging in an MRI system, and, more particularly for facilitating estimation of tensors and tensor-derived measures in diffusional kurtosis imaging (DKI). For example, DKI can facilitate a characterization of non-Gaussian diffusion of water molecules in biological tissues. The diffusion and kurtosis tensors parameterizing the DKI model can typically be estimated via unconstrained least squares (LS) methods. In the presence of noise, motion, and imaging artifacts, these methods can be prone to producing physically and/or biologically implausible tensor estimates. The exemplary embodiments of the present disclosure can address at least this deficiency by formulating an exemplary estimation problem, e.g., as linearly constrained linear LS, where the constraints can ensure acceptable tensor estimates.
    • 可以提供示例性方法,系统和计算机可访问介质,用于通过接收与至少一个扩散加权图像相关的数据来确定扩散峰度的度量,并且使用闭合的方法确定作为接收数据的函数的扩散峰度的度量 形式解决程序。 根据本公开的某些示例性实施例,本文提供了用于例如在MRI系统中成像的计算机可访问介质,系统和方法,并且更具体地,用于促进扩散峭度成像中的张量和张量导出测量的估计 (DKI)。 例如,DKI可以促进水分子在生物组织中的非高斯扩散的表征。 参数化DKI模型的扩散和峰度张量通常可以通过非约束最小二乘法(LS)方法估计。 在存在噪声,运动和成像伪像的情况下,这些方法可能容易产生物理和/或生物学不可信的张量估计。 本公开的示例性实施例可以通过制定示例性估计问题(例如线性约束线性LS)来解决至少该缺陷,其中约束可以确保可接受的张量估计。
    • 2. 发明申请
    • System, Method and Computer Accessible Medium for Providing Real-Time Diffusional Kurtosis Imaging and for Facilitating Estimation of Tensors and Tensor- Derived Measures in Diffusional Kurtosis Imaging
    • 系统,方法和计算机可访问介质,用于提供实时扩散性血液饱和成像和促进传感器估计和弥漫性高血压成像中的传感器测量
    • US20120002851A1
    • 2012-01-05
    • US13022488
    • 2011-02-07
    • Jens JensenJoseph HelpernAli TabeshEls Fieremans
    • Jens JensenJoseph HelpernAli TabeshEls Fieremans
    • G06K9/00
    • G01R33/56341
    • Exemplary method, system, and computer-accessible medium can be provided for determining a measure of diffusional kurtosis by receiving data relating to at least one diffusion weighted image, and determining a measure of a diffusional kurtosis as a function of the received data using a closed form solution procedure. In accordance with certain exemplary embodiments of the present disclosure, provided herein are computer-accessible medium, systems and methods for, e.g., imaging in an MRI system, and, more particularly for facilitating estimation of tensors and tensor-derived measures in diffusional kurtosis imaging (DKI). For example, DKI can facilitate a characterization of non-Gaussian diffusion of water molecules in biological tissues. The diffusion and kurtosis tensors parameterizing the DKI model can typically be estimated via unconstrained least squares (LS) methods. In the presence of noise, motion, and imaging artifacts, these methods can be prone to producing physically and/or biologically implausible tensor estimates. The exemplary embodiments of the present disclosure can address at least this deficiency by formulating an exemplary estimation problem, e.g., as linearly constrained linear LS, where the constraints can ensure acceptable tensor estimates.
    • 可以提供示例性方法,系统和计算机可访问介质,用于通过接收与至少一个扩散加权图像相关的数据来确定扩散峰度的度量,并且使用闭合的方法确定作为接收数据的函数的扩散峰度的度量 形式解决程序。 根据本公开的某些示例性实施例,本文提供了用于例如在MRI系统中成像的计算机可访问介质,系统和方法,并且更具体地,用于促进扩散峭度成像中的张量和张量导出测量的估计 (DKI)。 例如,DKI可以促进水分子在生物组织中的非高斯扩散的表征。 参数化DKI模型的扩散和峰度张量通常可以通过非约束最小二乘法(LS)方法估计。 在存在噪声,运动和成像伪像的情况下,这些方法可能容易产生物理和/或生物学不可信的张量估计。 本公开的示例性实施例可以通过制定示例性估计问题(例如线性约束线性LS)来解决至少该缺陷,其中约束可以确保可接受的张量估计。