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    Systems, devices, and methods for diffusion tractography
    1.
    发明授权
    Systems, devices, and methods for diffusion tractography 有权
    用于扩散造影的系统，装置和方法

    公开(公告)号：US07881878B2

    公开(公告)日：2011-02-01

    申请号：US11398189

    申请日：2006-04-05

    申请人： Nicolas Burrus ,  Mariappan S. Nadar

    发明人： Nicolas Burrus ,  Mariappan S. Nadar

    IPC分类号： G01N31/00

    CPC分类号： G01R33/56341 ,  G01R33/5608 ,  G06F19/00 ,  G06F19/321

    摘要： Certain exemplary embodiments comprise a method, which can comprise automatically causing a representation of body tissue to be rendered. The body tissue can be tracked via clusters. The clusters each can comprise a predetermined number of particles. Each particle of a particular cluster can be representative of a discreet path associated with the particular cluster in a tensor field.

    摘要翻译： 某些示例性实施例包括一种方法，其可以包括自动地使呈现身体组织的表示。 身体组织可以通过簇跟踪。 簇可以包括预定数量的颗粒。 特定簇的每个粒子可以代表与张量场中的特定簇相关联的谨慎路径。

    Generalized Approximate Message Passing Algorithms for Sparse Magnetic Resonance Imaging Reconstruction
    2.
    发明申请
    Generalized Approximate Message Passing Algorithms for Sparse Magnetic Resonance Imaging Reconstruction 有权
    广义近似消息传递算法用于稀疏磁共振成像重建

    公开(公告)号：US20160247299A1

    公开(公告)日：2016-08-25

    申请号：US14630712

    申请日：2015-02-25

    申请人： Jin Tan ,  Boris Mailhe ,  Qiu Wang ,  Mariappan S. Nadar

    发明人： Jin Tan ,  Boris Mailhe ,  Qiu Wang ,  Mariappan S. Nadar

    IPC分类号： G06T11/00 ,  G06T7/00

    CPC分类号： G06T11/003 ,  G01R33/5611 ,  G06T7/0012 ,  G06T2207/10088

    摘要： A method for reconstructing magnetic resonance imaging data includes acquiring a measurement dataset using a magnetic resonance imaging device and determining an estimated image dataset based on the measurement dataset. An iterative reconstruction process is performed to refine the estimated image dataset. Each iteration of the iterative reconstruction process comprises: updating the measurement dataset and a sparse coefficient dataset based on the estimated image dataset and a plurality of belief propagation terms, incorporating a noise prior dataset into the measurement dataset, incorporating a sparsity prior dataset into the sparse coefficient dataset, updating the plurality of belief propagation terms based on the measurement dataset and the sparsity prior dataset, and updating the estimated image dataset based on the plurality of belief propagation terms. A reconstructed image and confidence map are generated using the estimated image dataset.

    摘要翻译： 一种用于重建磁共振成像数据的方法包括使用磁共振成像装置获取测量数据集，并且基于测量数据集确定估计的图像数据集。 执行迭代重建过程以细化估计的图像数据集。 迭代重建过程的每次迭代包括：基于估计的图像数据集和多个置信传播项更新测量数据集和稀疏系数数据集，将噪声预先数据集合并入测量数据集，将稀疏性先验数据集合并入稀疏 系数数据集，基于测量数据集和稀疏性先验数据集更新多个置信传播项，以及基于多个置信传播项更新估计图像数据集。 使用估计的图像数据集生成重建图像和置信图。

    Zero communication block partitioning
    3.
    发明授权
    Zero communication block partitioning 有权
    零通信块分区

    公开(公告)号：US09286648B2

    公开(公告)日：2016-03-15

    申请号：US13950535

    申请日：2013-07-25

    申请人： Mariappan S. Nadar

    发明人： Alban Lefebvre ,  Axel Loewe ,  Mariappan S. Nadar ,  Jun Liu

    IPC分类号： G06K9/54 ,  G06T1/20 ,  G01R33/56

    CPC分类号： G06T1/20 ,  G01R33/5608

    摘要： A computer-implemented method for calculating a multi-dimensional wavelet transform in an image processing system comprising a plurality of computation units includes receiving multi-dimensional image data. An overlap value corresponding to a number of non-zero filter coefficients associated with the multi-dimensional wavelet transform is identified. Then the multi-dimensional image data is divided into a plurality of multi-dimensional arrays, wherein the multi-dimensional arrays overlap in each dimension by a number of pixels equal to the overlap value. A multi-dimensional wavelet transform is calculated for each multi-dimensional array, in parallel, across the plurality of computation units.

    摘要翻译： 一种用于在包括多个计算单元的图像处理系统中计算多维小波变换的计算机实现方法包括接收多维图像数据。 识别与多维小波变换相关联的非零滤波器系数的数量对应的重叠值。 然后，多维图像数据被分成多个多维阵列，其中多维阵列在每个维度上与等于重叠值的像素的数量重叠。 在多个计算单元中并行计算每个多维阵列的多维小波变换。

    MULTI-STAGE MAGNETIC RESONANCE RECONSTRUCTION FOR PARALLEL IMAGING APPLICATIONS
    4.
    发明申请
    MULTI-STAGE MAGNETIC RESONANCE RECONSTRUCTION FOR PARALLEL IMAGING APPLICATIONS 有权
    并行成像应用的多级磁共振重建

    公开(公告)号：US20140133724A1

    公开(公告)日：2014-05-15

    申请号：US14054003

    申请日：2013-10-15

    申请人： Jun Liu ,  Zhili Yang ,  Mariappan S. Nadar ,  Nirmal Janardhanan ,  Michael Zenge ,  Edgar Mueller ,  Qiu Wang ,  Axel Loewe

    发明人： Jun Liu ,  Zhili Yang ,  Mariappan S. Nadar ,  Nirmal Janardhanan ,  Michael Zenge ,  Edgar Mueller ,  Qiu Wang ,  Axel Loewe

    IPC分类号： G06T11/00

    CPC分类号： G01R33/5611

    摘要： A computer-implemented method for reconstruction of a magnetic resonance image includes acquiring a first incomplete k-space data set comprising a plurality of first k-space lines spaced according to an acceleration factor and one or more calibration lines. A parallel imaging reconstruction technique is applied to the first incomplete k-space data to determine a plurality of second k-space lines not included in the first incomplete k-space data set, thereby yielding a second incomplete k-space data set. Then, the parallel imaging reconstruction technique is applied to the second incomplete k-space data to determine a plurality of third k-space lines not included in the second incomplete k-space data, thereby yielding a complete k-space data set.

    摘要翻译： 用于重建磁共振图像的计算机实现的方法包括获取包括根据加速因子和一个或多个校准线间隔开的多个第一k空间线的第一不完整k空间数据集。 将并行成像重建技术应用于第一不完整k空间数据以确定未包括在第一不完整k空间数据集中的多个第二k空间线，从而产生第二不完整k空间数据集。 然后，将并行成像重构技术应用于第二不完整k空间数据，以确定不包括在第二不完整k空间数据中的多个第三k空间线，从而产生完整的k空间数据集。

    Generalized approximate message passing algorithms for sparse magnetic resonance imaging reconstruction
    7.
    发明授权
    Generalized approximate message passing algorithms for sparse magnetic resonance imaging reconstruction 有权
    用于稀疏磁共振成像重建的广义近似消息传递算法

    公开(公告)号：US09542761B2

    公开(公告)日：2017-01-10

    申请号：US14630712

    申请日：2015-02-25

    申请人： Jin Tan ,  Boris Mailhe ,  Qiu Wang ,  Mariappan S. Nadar

    发明人： Jin Tan ,  Boris Mailhe ,  Qiu Wang ,  Mariappan S. Nadar

    IPC分类号： G06K9/00 ,  G06T11/00 ,  G06T7/00 ,  A61B6/00

    CPC分类号： G06T11/003 ,  G01R33/5611 ,  G06T7/0012 ,  G06T2207/10088

    摘要： A method for reconstructing magnetic resonance imaging data includes acquiring a measurement dataset using a magnetic resonance imaging device and determining an estimated image dataset based on the measurement dataset. An iterative reconstruction process is performed to refine the estimated image dataset. Each iteration of the iterative reconstruction process comprises: updating the measurement dataset and a sparse coefficient dataset based on the estimated image dataset and a plurality of belief propagation terms, incorporating a noise prior dataset into the measurement dataset, incorporating a sparsity prior dataset into the sparse coefficient dataset, updating the plurality of belief propagation terms based on the measurement dataset and the sparsity prior dataset, and updating the estimated image dataset based on the plurality of belief propagation terms. A reconstructed image and confidence map are generated using the estimated image dataset.

    摘要翻译： 一种用于重建磁共振成像数据的方法包括使用磁共振成像装置获取测量数据集，并且基于测量数据集确定估计的图像数据集。 执行迭代重建过程以细化估计的图像数据集。 迭代重建过程的每次迭代包括：基于估计的图像数据集和多个置信传播项更新测量数据集和稀疏系数数据集，将噪声预先数据集合并入测量数据集，将稀疏性先验数据集合并入稀疏 系数数据集，基于测量数据集和稀疏性先验数据集更新多个置信传播项，以及基于多个置信传播项更新估计图像数据集。 使用估计的图像数据集生成重建图像和置信图。

    MRI reconstruction with motion-dependent regularization
    8.
    发明授权
    MRI reconstruction with motion-dependent regularization 有权
    MRI重建与运动相关正则化

    公开(公告)号：US09482732B2

    公开(公告)日：2016-11-01

    申请号：US14065498

    申请日：2013-10-29

    申请人： Nicolas Chesneau ,  Nirmal Janardhanan ,  Jun Liu ,  Mariappan S. Nadar ,  Qiu Wang ,  Zhili Yang

    发明人： Nicolas Chesneau ,  Nirmal Janardhanan ,  Jun Liu ,  Mariappan S. Nadar ,  Qiu Wang ,  Zhili Yang

    IPC分类号： G06K9/00 ,  G01R33/563 ,  G01R33/48 ,  G01R33/565 ,  G01R33/561

    CPC分类号： G01R33/56308 ,  G01R33/4824 ,  G01R33/5611 ,  G01R33/56509

    摘要： A method of image reconstruction for a magnetic resonance imaging (MRI) system includes obtaining k-space scan data captured by the MRI system, the k-space scan data being representative of an undersampled region over time, iteratively reconstructing preliminary dynamic images for the undersampled region from the k-space scan data via optimization of a first instance of a minimization problem, the minimization problem including a regularization term weighted by a weighting parameter array, generating a motion determination indicative of an extent to which each location of the undersampled region exhibits motion over time based on the preliminary dynamic images, and iteratively reconstructing motion-compensated dynamic images for the region from the k-space scan data via optimization of a second instance of the minimization problem, the second instance having the weighting parameter array altered as a function of the motion determination.

    摘要翻译： 用于磁共振成像（MRI）系统的图像重建方法包括获得由MRI系统捕获的k空间扫描数据，k空间扫描数据代表欠采样区域随着时间的推移，迭代地重建欠采样的初步动态图像 该最小化问题包括由加权参数阵列加权的正则化项，产生表示欠采样区域的每个位置显示的程度的运动确定 基于初步动态图像的时间运动，以及经由最小化问题的第二实例的优化从k空间扫描数据迭代地重建该区域的运动补偿动态图像，将具有加权参数阵列的第二实例改变为 运动确定的功能。

    Method for exploiting structure in sparse domain for magnetic resonance image reconstruction
    10.
    发明授权
    Method for exploiting structure in sparse domain for magnetic resonance image reconstruction 有权
    用于磁共振图像重构的稀疏结构开发方法

    公开(公告)号：US08760572B2

    公开(公告)日：2014-06-24

    申请号：US12942427

    申请日：2010-11-09

    申请人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

    发明人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

    IPC分类号： H04N7/12 ,  G06K9/00

    CPC分类号： G01R33/5608 ,  G06T11/006 ,  G06T2211/424

    摘要： A method for constructing an image includes acquiring image data in a first domain. The acquired image data is transformed from the first domain into a second domain in which the acquired image data exhibits a high degree of sparsity. An initial set of transform coefficients is approximated for transforming the image data from the second domain into a third domain in which the image may be displayed. The approximated initial set of transform coefficients is updated based on a weighing of where substantial transform coefficients are likely to be located relative to the initial set of transform coefficients. An image is constructed in the third domain based on the updated set of transform coefficients. The constructed image is displayed.

    摘要翻译： 一种用于构建图像的方法包括获取第一域中的图像数据。 所获取的图像数据从第一域变换到第二域，其中所获取的图像数据表现出高度的稀疏性。 近似变换系数的初始集合，用于将来自第二域的图像数据变换成可以显示图像的第三域。 基于对相对于初始变换系数集合可能存在实质变换系数的权重来更新近似初始变换系数集合。 基于更新的变换系数组，在第三域中构建图像。 显示构图。