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    Systems and Methods for Efficiently Generating Magnetic Resonance Images from Incomplete Data
    1.
    发明申请
    Systems and Methods for Efficiently Generating Magnetic Resonance Images from Incomplete Data 审中-公开
    从不完整的数据有效地产生磁共振图像的系统和方法

    公开(公告)号：US20150309136A1

    公开(公告)日：2015-10-29

    申请号：US14694621

    申请日：2015-04-23

    申请人： Yunhong Shu ,  Armando Manduca ,  Joshua D. Trzasko ,  Matthew A. Bernstein

    发明人： Yunhong Shu ,  Armando Manduca ,  Joshua D. Trzasko ,  Matthew A. Bernstein

    IPC分类号： G01R33/48 ,  G01R33/36 ,  G01R33/561 ,  G01R33/385 ,  G01R33/56

    CPC分类号： G01R33/4826 ,  G01R33/5611

    摘要： Systems and methods for efficiently generating MR images are provided. The method comprises acquiring k-space MR data, reconstructing an MR image from the k-space MR data, and generating the MR image. The MR image is reconstructed using an alternative-direction-method-of-multiplier (ADMM) strategy that decomposes an optimization problem into subproblems, and at least one of the subproblems is further decomposed into small problems. The further decomposition is based on Woodbury matrix identity and uses a diagonal preconditioner based on non-Toeplitz models.

    摘要翻译： 提供了有效产生MR图像的系统和方法。 该方法包括获取k空间MR数据，从k空间MR数据重建MR图像，以及生成MR图像。 使用将优化问题分解为子问题的替代方向乘法器（ADMM）策略重构MR图像，并且至少一个子问题进一步分解为小问题。 进一步分解是基于Woodbury矩阵身份，并使用基于非Toeplitz模型的对角预处理器。

    System and method for medical image reconstruction and image series denoising using local low rank promotion
    3.
    发明授权
    System and method for medical image reconstruction and image series denoising using local low rank promotion 有权
    用于医学图像重建的系统和方法以及使用本地低级推广的图像序列去噪

    公开(公告)号：US08989465B2

    公开(公告)日：2015-03-24

    申请号：US13743465

    申请日：2013-01-17

    申请人： Joshua D. Trzasko ,  Armando Manduca

    发明人： Joshua D. Trzasko ,  Armando Manduca

    IPC分类号： G06K9/00 ,  G06T11/00

    CPC分类号： G06T11/003 ,  G06T11/006 ,  G06T2211/412 ,  G06T2211/424

    摘要： A method for reconstructing a time series of images from data acquired with a medical imaging system is provided. Data is acquired with the medical imaging system, and a set of image blocks that defines the location and size of each of a plurality of image blocks in the image domain is then selected. The acquired data and selected image block set are then used to jointly estimate a plurality of images that form a time series of images while promoting locally-low rank structure in the images.

    摘要翻译： 提供了一种用于从用医学成像系统获取的数据重建图像的时间序列的方法。 然后，利用医学成像系统获取数据，然后选择定义图像域中的多个图像块中的每一个的位置和大小的一组图像块。 所获取的数据和所选择的图像块集合然后用于联合估计形成图像的时间序列的多个图像，同时促进图像中的局部低秩结构。

    SYSTEM AND METHOD FOR MEDICAL IMAGE RECONSTRUCTION AND IMAGE SERIES DENOISING USING LOCAL LOW RANK PROMOTION
    5.
    发明申请
    SYSTEM AND METHOD FOR MEDICAL IMAGE RECONSTRUCTION AND IMAGE SERIES DENOISING USING LOCAL LOW RANK PROMOTION 有权
    医学图像重构系统与方法及使用本地低排名推广的图像系列

    公开(公告)号：US20130182930A1

    公开(公告)日：2013-07-18

    申请号：US13743465

    申请日：2013-01-17

    申请人： Joshua D. Trzasko ,  Armando Manduca

    发明人： Joshua D. Trzasko ,  Armando Manduca

    IPC分类号： G06T11/00

    CPC分类号： G06T11/003 ,  G06T11/006 ,  G06T2211/412 ,  G06T2211/424

    摘要： A method for reconstructing a time series of images from data acquired with a medical imaging system is provided. Data is acquired with the medical imaging system, and a set of image blocks that defines the location and size of each of a plurality of image blocks in the image domain is then selected. The acquired data and selected image block set are then used to jointly estimate a plurality of images that form a time series of images while promoting locally-low rank structure in the images.

    摘要翻译： 提供了一种用于从用医学成像系统获取的数据重建图像的时间序列的方法。 然后，利用医学成像系统获取数据，然后选择定义图像域中的多个图像块中的每一个的位置和大小的一组图像块。 所获取的数据和所选择的图像块集合然后用于联合估计形成图像的时间序列的多个图像，同时促进图像中的局部低秩结构。

    System and Method for Generating Spatial Maps of Mechanical Parameters Using Graph-Cut Based Optimization
    6.
    发明申请
    System and Method for Generating Spatial Maps of Mechanical Parameters Using Graph-Cut Based Optimization 审中-公开
    使用基于图形的优化来生成机械参数的空间映射的系统和方法

    公开(公告)号：US20150309140A1

    公开(公告)日：2015-10-29

    申请号：US14689149

    申请日：2015-04-17

    申请人： Joshua D. Trzasko ,  Armando Manduca

    发明人： Joshua D. Trzasko ,  Armando Manduca

    IPC分类号： G01R33/54

    CPC分类号： G01R33/56358 ,  G01R33/5608

    摘要： A system and method for generating a spatial map of parameters that describe the mechanically-induced harmonic motion information present within a magnetic resonance elastography (MRE) data set is provided. A first temporal harmonic signal is estimated using a graph-cut based optimization strategy, and can subsequently be used to generate a the spatial map of mechanical parameters. The MRE data set is used to estimate the harmonic. The spatial map is of a mechanical parameter derived from the estimated harmonic.

    摘要翻译： 提供了一种用于生成描述在磁共振弹性成像（MRE）数据集内存在的机械感应谐波运动信息的参数的空间图的系统和方法。 使用基于图形的优化策略来估计第一时间谐波信号，并且随后可以用于生成机械参数的空间图。 MRE数据集用于估计谐波。 空间映射是从估计谐波导出的机械参数。

    Method for compressed sensing image reconstruction using a priori knowledge of spatial support
    7.
    发明授权
    Method for compressed sensing image reconstruction using a priori knowledge of spatial support 有权
    使用先验空间支持知识的压缩感测图像重建方法

    公开(公告)号：US08897515B2

    公开(公告)日：2014-11-25

    申请号：US12877638

    申请日：2010-09-08

    申请人： Joshua D Trzasko ,  Armando Manduca

    发明人： Joshua D Trzasko ,  Armando Manduca

    IPC分类号： G06K9/00 ,  G06T11/00

    CPC分类号： G06T11/006 ,  G06T2211/424 ,  G06T2211/436

    摘要： A method for image reconstruction that utilizes the benefits of compressed sensing (“CS”) while incorporating a priori knowledge of object spatial support into the image reconstruction is provided. Image data is acquired from a subject, for example, with a medical imaging system, such as a magnetic resonance imaging (“MRI”) system or a computed tomography (“CT”) system. An estimate of the spatial support of the subject is produced, for example, using a low resolution image of the subject, or an image reconstructed from undersampled image data in a traditional sense. An estimate image of the subject is also produced by using traditional image reconstruction methods on the acquired image data. An image of the subject is then reconstructed using the produced estimate image and produced spatial support estimate. This method allows for the reconstruction of quality images from undersampled image data in a computationally efficient manner.

    摘要翻译： 提供了一种利用压缩感知（“CS”）的优点，同时将对象空间支持的先验知识并入图像重建中的图像重建方法。 例如，利用诸如磁共振成像（“MRI”）系统或计算机断层扫描（“CT”）系统的医学成像系统从受试者获取图像数据。 产生对象的空间支持的估计，例如，使用对象的低分辨率图像，或从传统意义上的欠采样图像数据重建的图像。 通过对所获取的图像数据使用传统的图像重建方法也产生对象的估计图像。 然后使用所产生的估计图像重建受试者的图像并产生空间支持估计。 该方法允许以计算有效的方式重建来自欠采样图像数据的质量图像。

    Method for image reconstruction from undersampled medical imaging data
    8.
    发明授权
    Method for image reconstruction from undersampled medical imaging data 有权
    从欠采样的医学成像数据进行图像重建的方法

    公开(公告)号：US08310233B2

    公开(公告)日：2012-11-13

    申请号：US12705818

    申请日：2010-02-15

    申请人： Joshua D Trzasko ,  Armando Manduca

    发明人： Joshua D Trzasko ,  Armando Manduca

    IPC分类号： G01V3/00 ,  G06K9/00

    CPC分类号： G01R33/561 ,  G01R33/5608 ,  G01R33/5611

    摘要： A method for image reconstruction that utilizes a generalization of compressed sensing is provided. More particularly, a method for homotopic l0 minimization is provided, in which a series of subproblems that asymptotically approach a solution to the l0 minimization are iteratively solved. These subproblems include utilizing concave metric prior functionals in the traditional compressed sensing framework. Substantially undersampled image data is acquired from a subject, for example, with a medical imaging system, such as a magnetic resonance imaging (“MRI”) system or a computed tomography (“CT”) system. Using the provided method, undersampling on the order of around 96 percent can be achieved while still producing clinically acceptable images.

    摘要翻译： 提供了一种利用压缩感知泛化的图像重建方法。 更具体地，提供了一种用于同位素最小化的方法，其中迭代地解决渐近地接近10个最小化的解的一系列子问题。 这些子问题包括在传统的压缩感知框架中利用凹度度量先验函数。 例如使用诸如磁共振成像（MRI）系统或计算机断层摄影（CT）系统的医学成像系统从受试者获取基本欠采样的图像数据。 使用所提供的方法，可以在仍然产生临床可接受的图像的同时实现大约96％的低采样。

    METHOD FOR COMPRESSED SENSING IMAGE RECONSTRUCTION USING A PRIORI KNOWLEDGE OF SPATIAL SUPPORT
    10.
    发明申请
    METHOD FOR COMPRESSED SENSING IMAGE RECONSTRUCTION USING A PRIORI KNOWLEDGE OF SPATIAL SUPPORT 有权
    使用空间支持优先知识的压缩感测图像重建方法

    公开(公告)号：US20110058719A1

    公开(公告)日：2011-03-10

    申请号：US12877638

    申请日：2010-09-08

    申请人： Joshua D. Trzasko ,  Armando Manduca

    发明人： Joshua D. Trzasko ,  Armando Manduca

    IPC分类号： G06K9/00

    CPC分类号： G06T11/006 ,  G06T2211/424 ,  G06T2211/436

    摘要： A method for image reconstruction that utilizes the benefits of compressed sensing (“CS”) while incorporating a priori knowledge of object spatial support into the image reconstruction is provided. Image data is acquired from a subject, for example, with a medical imaging system, such as a magnetic resonance imaging (“MRI”) system or a computed tomography (“CT”) system. An estimate of the spatial support of the subject is produced, for example, using a low resolution image of the subject, or an image reconstructed from undersampled image data in a traditional sense. An estimate image of the subject is also produced by using traditional image reconstruction methods on the acquired image data. An image of the subject is then reconstructed using the produced estimate image and produced spatial support estimate. This method allows for the reconstruction of quality images from undersampled image data in a computationally efficient manner.

    摘要翻译： 提供了一种利用压缩感知（“CS”）的优点，同时将对象空间支持的先验知识并入图像重建中的图像重建方法。 例如，利用诸如磁共振成像（“MRI”）系统或计算机断层扫描（“CT”）系统的医学成像系统从受试者获取图像数据。 产生对象的空间支持的估计，例如，使用对象的低分辨率图像，或从传统意义上的欠采样图像数据重建的图像。 通过对所获取的图像数据使用传统的图像重建方法也产生对象的估计图像。 然后使用所产生的估计图像重建受试者的图像并产生空间支持估计。 该方法允许以计算有效的方式重建来自欠采样图像数据的质量图像。