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公开(公告)号：US07319788B2
公开(公告)日：2008-01-15
申请号：US10430293
申请日：2003-05-07
申请人： J. Ross Mitchell , T. Chen Fong , Hongmei Zhu
发明人： J. Ross Mitchell , T. Chen Fong , Hongmei Zhu
IPC分类号： G06K9/34
CPC分类号： G06K9/00523 , G06K9/6253
摘要： The present invention relates to a method for visualizing ST data based on principal component analysis. ST data indicative of a plurality of local S spectra, each local S spectrum corresponding to an image point of an image of an object are received. In a first step principal component axes of each local S spectrum are determined. This step is followed by the determination of a collapsed local S spectrum by projecting a magnitude of the local S spectrum onto at least one of its principal component axes, thus reducing the dimensionality of the S spectrum. After determining a weight function capable of distinguishing frequency components within a frequency band a texture map for display is generated by calculating a scalar value from each principal component of the collapsed S spectrum using the weight function and assigning the scalar value to a corresponding position with respect to the image. The visualization method according to the invention is a highly beneficial tool for image analysis substantially retaining local frequency information but not requiring prior knowledge of frequency content of an image. Employment of the visualization method according to the invention is highly beneficial, for example, for motion artifact suppression in MRI image data, texture analysis and disease specific tissue segmentation.
摘要翻译： 本发明涉及一种基于主成分分析可视化ST数据的方法。 表示多个局部S光谱的ST数据，接收对应于物体的图像的像点的每个局部S光谱。 在第一步中，确定每个局部S谱的主分量轴。 该步骤之后是通过将局部S谱的幅度投影到其主分量轴的至少一个上来确定折叠的局部S谱，从而降低S谱的维数。 在确定能够区分频带内的频率分量的加权函数之后，通过使用加权函数从折叠的S谱的每个主分量计算标量值来生成用于显示的纹理图，并且将标量值分配给相应的位置 到图像。 根据本发明的可视化方法是用于图像分析的非常有益的工具，其基本上保持本地频率信息，但不需要对图像的频率内容的事先知识。 使用根据本发明的可视化方法是非常有益的，例如，用于MRI图像数据中的运动伪影抑制，纹理分析和疾病特异性组织分割。
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2.发明授权公开(公告)号：US07251379B2
公开(公告)日：2007-07-31
申请号：US10430294
申请日：2003-05-07
申请人： J. Ross Mitchell , T. Chen Fong , Robert Brown , Hongmei Zhu
发明人： J. Ross Mitchell , T. Chen Fong , Robert Brown , Hongmei Zhu
IPC分类号： G06K9/54
CPC分类号： G06T7/0012 , G06F17/14 , G06T7/42 , G06T2207/10072 , G06T2207/30004
摘要： The present invention relates to a method and system for distributed computing an S transform dataset of multidimensional image data of an object. The multidimensional image data are fast Fourier transformed into Fourier domain producing a Fourier spectrum. The respective Fourier frequencies are then partitioned into a plurality of portions of frequencies for simultaneously processing. Processing of each of the plurality of portions of the Fourier frequencies is assigned to a respective processor of a plurality of processors. The Fourier spectrum of multidimensional image data and each of the plurality of portions of the Fourier frequencies is transmitted to the respective processor. The portions of the Fourier frequencies are then simultaneously processed in order to produce the S transform dataset. The S transform data are then collected and stored. The method and system for computing the S transform according to the invention provides a substantially increased computation speed enabling use of the S transform for practical applications in a clinical setting.
摘要翻译： 本发明涉及一种用于分布式计算物体的多维图像数据的S变换数据集的方法和系统。 多维图像数据被快速傅里叶变换成傅立叶域产生傅里叶谱。 然后将各个傅里叶频率分割成多个频率部分，以便同时处理。 将傅立叶频率的多个部分中的每一个的处理分配给多个处理器的相应处理器。 将多维图像数据和傅立叶频率的多个部分中的每一个的傅里叶谱发送到相应的处理器。 然后，对傅里叶频率的部分进行同时处理，以产生S变换数据集。 然后收集并存储S变换数据。 根据本发明的用于计算S变换的方法和系统提供了显着提高的计算速度，使得能够在临床设置中实际应用S变换。
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3.发明授权公开(公告)号：US07245786B2
公开(公告)日：2007-07-17
申请号：US10430204
申请日：2003-05-07
CPC分类号： G01R33/4806 , G01R33/56 , G06K9/00503
摘要： The present invention relates to a method for filtering time-varying MR signal data prior to image reconstruction. A one-dimensional FT is applied to the time-varying MR signal data along each frequency-encode line of k space. The phase p of each complex pair (R, I) of the FT transformed data is calculated to create a phase profile for each frequency-encode line. This process is repeated for all time points of the time-varying MR signal data. The time course of each point within the phase profile is then transformed into Stockwell domain producing ST spectra. Frequency component magnitudes indicative of an artifact are determined and replaced with a predetermined frequency component magnitude. Each of the ST spectra is then collapsed into a one-dimensional function. New real and imaginary values (R′, I′) of the complex Fourier data are calculated based on the collapsed ST spectra which are transformed using one-dimensional inverse Fourier transformation for producing filtered time-varying MR signal data. The method for filtering time-varying MR signal data is highly advantageous by easily identifying high-frequency artifacts within the ST spectrum and filtering only frequency components near the artifacts. Therefore, high-frequency artifacts are substantially removed while the frequency content of the remaining signal is preserved, enabling for example detection of subtle frequency changes occurring over time.
摘要翻译： 本发明涉及一种在图像重建之前对时变MR信号数据进行滤波的方法。 将一维FT应用于沿k空间的每个频率编码行的时变MR信号数据。 计算FT变换数据的每个复数对（R，I）的相位p，以产生每个频率编码行的相位曲线。 针对时变MR信号数据的所有时间点重复该过程。 然后将相位曲线内的每个点的时间过程转换成产生ST谱的斯托克韦尔域。 确定指示伪像的频率分量幅度，并用预定的频率分量量级代替。 然后将每个ST光谱折叠成一维函数。 基于使用一维逆傅里叶变换变换来生成经过滤波的时变MR信号数据的折叠ST频谱计算复数傅里叶数据的新实数值和虚数值（R'，I'）。 用于过滤时变MR信号数据的方法通过容易地识别ST频谱内的高频伪像并仅对伪像附近的频率分量进行滤波是非常有利的。 因此，在保持剩余信号的频率内容的同时，基本上去除了高频伪影，能够实现例如随时间发生的微妙频率变化的检测。
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4.发明授权公开(公告)号：US07502526B2
公开(公告)日：2009-03-10
申请号：US11826504
申请日：2007-07-16
CPC分类号： G01R33/4806 , G01R33/56 , G06K9/00503
摘要： The present invention relates to a method for filtering time-varying MR signal data prior to image reconstruction. A one-dimensional FT is applied to the time-varying MR signal data along each frequency-encode line of k space. The phase p of each complex pair (R,I) of the FT transformed data is calculated to create a phase profile for each frequency-encode line. This process is repeated for all time points of the time-varying MR signal data. The time course of each point within the phase profile is then transformed into Stockwell domain producing ST spectra. Frequency component magnitudes indicative of an artifact are determined and replaced with a predetermined frequency component magnitude. Each of the ST spectra is then collapsed into a one-dimensional function. New real and imaginary values (R′,I′) of the complex Fourier data are calculated based on the collapsed ST spectra which are transformed using one-dimensional inverse Fourier transformation for producing filtered time-varying MR signal data. The method for filtering time-varying MR signal data is highly advantageous by easily identifying high-frequency artifacts within the ST spectrum and filtering only frequency components near the artifacts. Therefore, high-frequency artifacts are substantially removed while the frequency content of the remaining signal is preserved, enabling for example detection of subtle frequency changes occurring over time.
摘要翻译： 本发明涉及一种在图像重建之前对时变MR信号数据进行滤波的方法。 将一维FT应用于沿k空间的每个频率编码行的时变MR信号数据。 计算FT变换数据的每个复数对（R，I）的相位p，以产生每个频率编码行的相位曲线。 针对时变MR信号数据的所有时间点重复该过程。 然后将相位曲线内的每个点的时间过程转换成产生ST谱的斯托克韦尔域。 确定指示伪像的频率分量幅度，并用预定的频率分量量级代替。 然后将每个ST光谱折叠成一维函数。 基于使用一维逆傅里叶变换变换来生成经过滤波的时变MR信号数据的折叠ST频谱计算复数傅里叶数据的新实数值和虚数值（R'，I'）。 用于过滤时变MR信号数据的方法通过容易地识别ST频谱内的高频伪像并仅对伪像附近的频率分量进行滤波是非常有利的。 因此，在保持剩余信号的频率内容的同时，基本上去除了高频伪影，能够实现例如随时间发生的微妙频率变化的检测。
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公开(公告)号：US06850062B2
公开(公告)日：2005-02-01
申请号：US10430295
申请日：2003-05-07
IPC分类号： G01R33/48 , G01R33/56 , G01R33/565 , G01R33/567 , G01V3/00
CPC分类号： G01R33/56 , G01R33/4806 , G01R33/56509
摘要： The present invention relates to a method for processing magnetic resonance signal data. magnetic resonance signal data in dependence upon a magnetic resonance signal time series are received. The magnetic resonance signal data are then transformed into a time-frequency Stockwell domain using a localizing time window having a frequency dependent window width in order to provide multi-resolution in the time-frequency domain. The Stockwell transformed magnetic resonance signal data are then processed in the Stockwell domain, for example, filtered based on time-frequency information of the Stockwell transformed magnetic resonance signal data. The processed Stockwell transformed magnetic resonance signal data are then transformed into Fourier domain by summing the Stockwell transformed magnetic resonance signal data over time indices of the Stockwell domain. In a further step the Fourier transformed magnetic resonance signal data are then transformed into time domain using inverse Fourier transformation. In another embodiment the method for processing magnetic resonance signals is extended for processing two-dimensional magnetic resonance signal image data in a space-frequency Stockwell domain. The method for processing magnetic resonance signals according to the invention using the Stockwell transform overcomes many limitations of the Fourier framework of existing magnetic resonance signal processing tools. It is highly advantageous by providing frequency and time/space information while keeping a close connection with the Fourier formalism, which allows implementation of the method according to the present invention into existing Fourier-based signal processing tools.
摘要翻译： 本发明涉及一种处理磁共振信号数据的方法。 接收根据磁共振信号时间序列的磁共振信号数据。 然后使用具有频率依赖窗口宽度的定位时间窗将磁共振信号数据变换成时频斯托韦尔韦域，以便在时频域中提供多分辨率。 然后在Stockwell域中处理Stockwell变换的磁共振信号数据，例如，基于Stockwell变换的磁共振信号数据的时间 - 频率信息进行滤波。 然后将经处理的Stockwell变换的磁共振信号数据通过将Stockwell变换的磁共振信号数据随着Stockwell域的时间指数相加而被转换成傅立叶域。 在另一步骤中，傅里叶变换的磁共振信号数据然后使用傅立叶逆变换变换到时域。 在另一个实施例中，用于处理磁共振信号的方法被扩展用于处理空间频率的Stockwell域中的二维磁共振信号图像数据。 根据本发明使用Stockwell变换处理磁共振信号的方法克服了现有磁共振信号处理工具的傅立叶框架的许多限制。 通过提供频率和时间/空间信息来保持与傅里叶形式的密切联系是非常有利的，这允许根据本发明的方法实现到现有的基于傅里叶的信号处理工具中。
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