发明申请
US20120002851A1 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
有权
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
- 专利标题: 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
- 专利标题(中): 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
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申请号: US13022488申请日: 2011-02-07
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公开(公告)号: US20120002851A1公开(公告)日: 2012-01-05
- 发明人: Jens Jensen , Joseph Helpern , Ali Tabesh , Els Fieremans
- 申请人: Jens Jensen , Joseph Helpern , Ali Tabesh , Els Fieremans
- 申请人地址: US NY New York
- 专利权人: New York University
- 当前专利权人: New York University
- 当前专利权人地址: US NY New York
- 优先权: USPCT/US2009/053223 20090807
- 主分类号: G06K9/00
- IPC分类号: G06K9/00
摘要:
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.
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