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    • 8. 发明申请
    • Automatic optimization for ultrasound medical imaging
    • 超声医学影像自动优化
    • US20080021326A1
    • 2008-01-24
    • US11893015
    • 2007-08-13
    • Muge BakirciogluRobert SteinsConstantine Simopoulos
    • Muge BakirciogluRobert SteinsConstantine Simopoulos
    • A61B8/06
    • A61B8/06
    • Methods and systems are provided for automatic optimization for ultrasound medical imaging. In one approach, velocity values are unwrapped to avoid aliasing artifacts. Multi-dimensional phase unwrapping is applied to the velocity data. The unwrapped velocity information is used to optimize one or both of the velocity scale (e.g., pulse repetition frequency) and the imaging frequency. For optimizing the scale setting, the distribution of unwrapped velocities from a systolic time period of the heart cycle are used to identify the pulse repetition frequency. For optimizing the imaging frequency, a correlation as a function of depth shows the penetration depth for a given imaging frequency. In a dependent or independent approach, one or more thresholds for velocity or energy in flow imaging are adaptively selected as a function of an amount of clutter. Velocity or other energy information in addition to the clutter information may be used for selecting the thresholds. In yet another dependent or independent approach, displacement of an imaging plane or other change is detected and used to trigger an automatic update of an imaging parameter for a same or different mode.
    • 提供了用于超声医学成像自动优化的方法和系统。 在一种方法中,速度值被打开以避免混叠伪像。 将多维相位展开应用于速度数据。 展开的速度信息用于优化速度标度(例如,脉冲重复频率)和成像频率中的一个或两个。 为了优化刻度设置,使用从心脏周期的收缩时间段展开的速度的分布来识别脉冲重复频率。 为了优化成像频率,作为深度函数的相关性表示给定成像频率的穿透深度。 在依赖或独立的方法中,自动地选择流量成像中的速度或能量的一个或多个阈值作为杂波量的函数。 除杂波信息之外的速度或其他能量信息可以用于选择阈值。 在另一个依赖或独立的方法中,检测成像平面的位移或其他变化,并且用于触发相同或不同模式的成像参数的自动更新。
    • 9. 发明申请
    • Automatic optimization for ultrasound medical imaging
    • 超声医学影像自动优化
    • US20050131300A1
    • 2005-06-16
    • US10737204
    • 2003-12-15
    • Muge BakirciogluRobert SteinsConstantine Simopoulos
    • Muge BakirciogluRobert SteinsConstantine Simopoulos
    • A61B8/06
    • A61B8/06
    • Methods and systems are provided for automatic optimization for ultrasound medical imaging. In one approach, velocity values are unwrapped to avoid aliasing artifacts. Multi-dimensional phase unwrapping is applied to the velocity data. The unwrapped velocity information is used to optimize one or both of the velocity scale (e.g., pulse repetition frequency) and the imaging frequency. For optimizing the scale setting, the distribution of unwrapped velocities from a systolic time period of the heart cycle are used to identify the pulse repetition frequency. For optimizing the imaging frequency, a correlation as a function of depth shows the penetration depth for a given imaging frequency. In a dependent or independent approach, one or more thresholds for velocity or energy in flow imaging are adaptively selected as a function of an amount of clutter. Velocity or other energy information in addition to the clutter information may be used for selecting the thresholds. In yet another dependent or independent approach, displacement of an imaging plane or other change is detected and used to trigger an automatic update of an imaging parameter for a same or different mode.
    • 提供了用于超声医学成像自动优化的方法和系统。 在一种方法中,速度值被打开以避免混叠伪像。 将多维相位展开应用于速度数据。 展开的速度信息用于优化速度标度(例如,脉冲重复频率)和成像频率中的一个或两个。 为了优化刻度设置,使用从心脏周期的收缩时间段展开的速度的分布来识别脉冲重复频率。 为了优化成像频率,作为深度函数的相关性表示给定成像频率的穿透深度。 在依赖或独立的方法中,自动地选择流量成像中的速度或能量的一个或多个阈值作为杂波量的函数。 除杂波信息之外的速度或其他能量信息可以用于选择阈值。 在另一个依赖或独立的方法中,检测成像平面的位移或其他变化,并且用于触发相同或不同模式的成像参数的自动更新。
    • 10. 发明授权
    • Method and apparatus for processing images with curves
    • 用曲线处理图像的方法和装置
    • US06694057B1
    • 2004-02-17
    • US09492693
    • 2000-01-27
    • Michael I. MillerNavin KhanejaMuge Bakircioglu
    • Michael I. MillerNavin KhanejaMuge Bakircioglu
    • G06K946
    • G06K9/6204
    • A system according to the invention identifies image data points defining a curve. The method comprises the steps of determining a start point and an end point for the curve, establishing a search space that includes at least the start point, the end point, and other image data elements comprising the curve, and searching the search space using a dynamic programming algorithm to locate image data elements corresponding to the curve. Another embodiment consistent with the present invention identifies image data points defining a curve. The method comprises the steps of determining a start point and an end point for the curve, generating a model of the curve, establishing a search space that includes at least the start point, the end point, and other image data elements comprising the curve, and searching the search space using a dynamic programming algorithm and the model for the curve to locate image data elements corresponding to the curve. Yet another embodiment consistent with the present invention matches a first curve to a second curve. The method comprises the steps of identifying a first curve, identifying a second curve, generating a higher order distance measure for comparing the first curve and the second curve, and matching the first curve to the second curve using the higher order distance measure.
    • 根据本发明的系统识别定义曲线的图像数据点。 该方法包括以下步骤:确定曲线的起点和终点,建立至少包括起点,终点和包括曲线的其他图像数据元素的搜索空间,并使用 动态编程算法来定位对应于曲线的图像数据元素。 与本发明一致的另一实施例识别定义曲线的图像数据点。 该方法包括以下步骤:确定曲线的起始点和终点,生成曲线的模型,建立搜索空间,该搜索空间至少包括起始点,终点和包括该曲线的其他图像数据元素, 并使用动态规划算法搜索搜索空间,并且用于曲线的模型来定位与该曲线相对应的图像数据元素。 符合本发明的另一个实施例将第一曲线与第二曲线相匹配。 该方法包括以下步骤:识别第一曲线,识别第二曲线,产生用于比较第一曲线和第二曲线的较高阶距离度量,以及使用较高阶距离度量将第一曲线与第二曲线匹配。