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1.发明授权MR diffusion weighted method and system providing microstructural information of a biological target using SINe cardinal (SINC) function and q-space sampling 有权使用SINe基数（SINC）函数和q空间取样提供生物靶的微结构信息的MR扩散加权方法和系统公开(公告)号：US08564289B2
公开(公告)日：2013-10-22
申请号：US12694429
申请日：2010-01-27
IPC分类号： G01R33/48
CPC分类号： G01R33/56341
摘要： A method is adapted for providing microstructural information of a biological target from a plurality of diffusion weighted MR images corresponding to a specific area of the biological target. Each of the diffusion weighted MR images is obtained using a respective q-space sampling vector and is sampled at a plurality of sample points thereof to obtain a group of diffusion weighted MR image data. The diffusion weighted MR image data are processed to obtain a spin distribution function from which the microstructural information of the biological target can be obtained.
摘要翻译： 一种方法适于从对应于该生物学目标的特定区域的多个扩散加权MR图像提供生物学目标的微结构信息。 使用各自的q空间采样矢量获得每个扩散加权MR图像，并在其多个采样点采样，以获得一组扩散加权的MR图像数据。 对扩散加权的MR图像数据进行处理以获得自动分布函数，从而获得生物靶标的微结构信息。
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2.发明申请VOXEL-BASED TRANSFORMATION METHOD FOR TRANSFORMING DIFFUSION MRI DATA AND GROUPS TEST METHOD USING THE SAME 有权用于改变扩散MRI数据和组合测试方法的基于VOXEL的变换方法公开(公告)号：US20130259340A1
公开(公告)日：2013-10-03
申请号：US13524704
申请日：2012-06-15
IPC分类号： G06K9/00
CPC分类号： G01R33/56341
摘要： A voxel-based transformation method includes: a) obtaining a MRI dataset in a subject space associated with subject voxel coordinates, subject sampling directions, and subject voxel spin amounts, and a dataset of a co-registration template associated with template voxel coordinates, each subject voxel coordinate corresponding to a template voxel coordinate according to a mapping function; b) through an inverse of the mapping function, obtaining subject voxel coordinates and a Jacobian matrix; and c) obtaining template voxel spin amounts, each being a function of a template sampling direction and a template voxel coordinate, using the Jacobian matrix and image data.
摘要翻译： 基于体素的变换方法包括：a）在与主体体素坐标，主体抽样方向和主体体素自旋量相关联的对象空间中获得MRI数据集，以及与模板体元坐标相关联的共同注册模板的数据集，每个 根据映射函数对应于模板体素坐标的主体体素坐标; b）通过映射函数的逆，获得主体体素坐标和雅可比矩阵; 以及c）使用雅可比矩阵和图像数据获得每个模板体素自旋量，其为模板采样方向和模板体素坐标的函数。
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3.发明授权Transformation method for diffusion spectrum imaging using large deformation diffeomorphic metric mapping 有权使用大变形变形度量映射的扩散光谱成像的变换方法公开(公告)号：US09047695B2
公开(公告)日：2015-06-02
申请号：US13644211
申请日：2012-10-03
申请人： Isaac Wen-Yih Tseng , Yung-Chin Hsu
发明人： Isaac Wen-Yih Tseng , Yung-Chin Hsu
CPC分类号： G06T11/003 , G06T7/0014 , G06T7/337 , G06T7/74 , G06T2207/10088 , G06T2207/20076 , G06T2207/30016
摘要： A transformation method for diffusion spectrum imaging includes: receiving an original DSI dataset and a template DSI dataset; computing an energy function; computing, for each time point, first-order and second-order derivatives of the energy function with respect to velocity fields in an image space and in a q-space; computing, for each time point, the velocity fields in the image space and in the q-space based upon the first-order and second-order derivatives; performing integration on the velocity fields over time to obtain a deformation field; and generating a transformed DSI dataset according to the deformation field.
摘要翻译： 扩散光谱成像的变换方法包括：接收原始DSI数据集和模板DSI数据集; 计算能量函数; 对于每个时间点，针对图像空间和q空间中的速度场计算能量函数的一阶和二阶导数; 对于每个时间点，基于一阶和二阶导数来计算图像空间和q空间中的速度场; 随着时间的推移在速度场上进行积分以获得变形场; 并根据变形场生成变换的DSI数据集。
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4.发明申请METHOD AND SYSTEM FOR PROVIDING MICROSTRUCTURAL INFORMATION OF A BIOLOGICAL TARGET 有权提供生物目标微结构信息的方法和系统公开(公告)号：US20100253337A1
公开(公告)日：2010-10-07
申请号：US12694429
申请日：2010-01-27
IPC分类号： G01R33/48
CPC分类号： G01R33/56341
摘要： A method is adapted for providing microstructural information of a biological target from a plurality of diffusion weighted MR images corresponding to a specific area of the biological target. Each of the diffusion weighted MR images is obtained using a respective q-space sampling vector and is sampled at a plurality of sample points thereof to obtain a group of diffusion weighted MR image data. The diffusion weighted MR image data are processed to obtain a spin distribution function from which the microstructural information of the biological target can be obtained.
摘要翻译： 一种方法适于从对应于该生物学目标的特定区域的多个扩散加权MR图像提供生物学目标的微结构信息。 使用各自的q空间采样矢量获得每个扩散加权MR图像，并在其多个采样点采样，以获得一组扩散加权的MR图像数据。 对扩散加权的MR图像数据进行处理以获得自动分布函数，从而获得生物靶标的微结构信息。
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5.发明授权Voxel-based transformation method for transforming diffusion MRI data and groups test method using the same 有权用于转换扩散MRI数据的体素变换方法和使用其的组测试方法公开(公告)号：US08849001B2
公开(公告)日：2014-09-30
申请号：US13524704
申请日：2012-06-15
IPC分类号： G06K9/00
CPC分类号： G01R33/56341
摘要： A voxel-based transformation method includes: a) obtaining a MRI dataset in a subject space associated with subject voxel coordinates, subject sampling directions, and subject voxel spin amounts, and a dataset of a co-registration template associated with template voxel coordinates, each subject voxel coordinate corresponding to a template voxel coordinate according to a mapping function; b) through an inverse of the mapping function, obtaining subject voxel coordinates and a Jacobian matrix; and c) obtaining template voxel spin amounts, each being a function of a template sampling direction and a template voxel coordinate, using the Jacobian matrix and image data.
摘要翻译： 基于体素的变换方法包括：a）在与主体体素坐标，主体抽样方向和主体体素自旋量相关联的对象空间中获得MRI数据集，以及与模板体元坐标相关联的共同注册模板的数据集，每个 根据映射函数对应于模板体素坐标的主体体素坐标; b）通过映射函数的逆，获得主体体素坐标和雅可比矩阵; 以及c）使用雅可比矩阵和图像数据获得每个模板体素自旋量，其为模板采样方向和模板体素坐标的函数。
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6.发明申请TRANSFORMATION METHOD FOR DIFFUSION SPECTRUM IMAGING USING LARGE DEFORMATION DIFFEOMORPHIC METRIC MAPPING 有权使用大变形非均匀公差映射进行扩散光谱成像的变换方法公开(公告)号：US20140044332A1
公开(公告)日：2014-02-13
申请号：US13644211
申请日：2012-10-03
申请人： Isaac Wen-Yih TSENG , Yung-Chin Hsu
发明人： Isaac Wen-Yih TSENG , Yung-Chin Hsu
IPC分类号： G06T11/00
CPC分类号： G06T11/003 , G06T7/0014 , G06T7/337 , G06T7/74 , G06T2207/10088 , G06T2207/20076 , G06T2207/30016
摘要： A transformation method for diffusion spectrum imaging includes: receiving an original DSI dataset and a template DSI dataset; computing an energy function; computing, for each time point, first-order and second-order derivatives of the energy function with respect to velocity fields in an image space and in a q-space; computing, for each time point, the velocity fields in the image space and in the q-space based upon the first-order and second-order derivatives;performing integration on the velocity fields over time to obtain a deformation field; and generating a transformed DSI dataset according to the deformation field.
摘要翻译： 扩散光谱成像的变换方法包括：接收原始DSI数据集和模板DSI数据集; 计算能量函数; 对于每个时间点，针对图像空间和q空间中的速度场计算能量函数的一阶和二阶导数; 对于每个时间点，基于一阶和二阶导数来计算图像空间和q空间中的速度场; 随着时间的推移在速度场上进行积分以获得变形场; 并根据变形场生成变换的DSI数据集。
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公开(公告)号：US08160339B2
公开(公告)日：2012-04-17
申请号：US12170386
申请日：2008-07-09
IPC分类号： G06K9/00
CPC分类号： G01R33/56341
摘要： A method of analyzing a diffusion-weighted magnetic resonance image is adapted to analyze an orientation distribution function ψ0 of nerve fibers at a vector in space. The method includes the following steps: (A) finding an orientation {circumflex over (μ)}a with the largest probability in the ODF ψ0; (B) maximizing a single fiber ODF ψ′; (C) analyzing the maximized single fiber ODF ψ′ to obtain quantitative information; (D) deducting the maximized single fiber ODF ψ′ obtained in step (B) from the entire ODF ψ0; and (E) stopping computation if the result obtained in step (D) is determined to be smaller than a predetermined value, and repeating steps (A), (B), (C), and (D) if otherwise.
摘要翻译： 分散扩散加权磁共振图像的方法适用于分析空间矢量中神经纤维的取向分布函数ψ0。 该方法包括以下步骤：（A）在ODFψ0中找到最大概率的方位{（f）） （B）使单纤维ODFψ'最大化; （C）分析最大单纤维ODFψ'以获得定量信息; （D）从整个ODFψ0中扣除在步骤（B）中获得的最大化单纤维ODFψ'; 如果确定步骤（D）中获得的结果小于预定值，则重复步骤（A），（B），（C）和（D），否则停止计算。
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公开(公告)号：US20090016590A1
公开(公告)日：2009-01-15
申请号：US12170386
申请日：2008-07-09
IPC分类号： G06K9/00
CPC分类号： G01R33/56341
摘要： A method of analyzing a diffusion-weighted magnetic resonance image is adapted to analyze an orientation distribution function ψ0 of nerve fibers at a vector in space. The method includes the following steps: (A) finding an orientation {circumflex over (μ)}a with the largest probability in the ODF ψ0; (B) maximizing a single fiber ODF ψ′; (C) analyzing the maximized single fiber ODF ψ′ to obtain quantitative information; (D) deducting the maximized single fiber ODF ψ′ obtained in step (B) from the entire ODF ψ0; and (E) stopping computation if the result obtained in step (D) is determined to be smaller than a predetermined value, and repeating steps (A), (B), (C), and (D) if otherwise.
摘要翻译： 扩散加权磁共振图像的分析方法适用于分析空间矢量中神经纤维的取向分布函数psi0。 该方法包括以下步骤：（A）在ODF psi0中找到最大概率的方向{（f）） （B）最大化单纤维ODF psi'; （C）分析最大单纤维ODF psi'以获得定量信息; （D）从整个ODF psi0中扣除在步骤（B）中获得的最大单纤维ODF psi'; 如果确定步骤（D）中获得的结果小于预定值，则重复步骤（A），（B），（C）和（D），否则停止计算。
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