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    • 2. 发明授权
    • Radial adaptive filter for metal artifact correction
    • 用于金属伪影校正的径向自适应滤波器
    • US07991243B2
    • 2011-08-02
    • US11815215
    • 2006-02-01
    • Matthieu BalHasan CelikKai EckLothar SpiesKrishna Subramanyan
    • Matthieu BalHasan CelikKai EckLothar SpiesKrishna Subramanyan
    • G06K9/40G06K9/00A61B6/00
    • G06T11/008
    • A diagnostic imaging system (10) corrects metal artifact streaks (38) emanating from a metal object (36) in a tomographic image (T). A first processor (40) reduces streaks (38) caused by mild artifacts by applying an adaptive filter (82). The filter (82) is perpendicularly oriented toward the center of the metal object (36). The weight of the filter (82) is a function of the local structure tensor and the vector pointing to the metal object (36). If it is determined that the strong artifacts are present in the image, a second processor (48) applies a sinogram completed image algorithm to correct for severe artifacts in the image. The sinogram completed image and adaptively filtered image are fused to a final corrected image. In the fusion process, highly corrupted tomographic regions are replaced by the result of the sinogram completed image and the remainder is replaced by the adaptively filtered image.
    • 诊断成像系统(10)校正在断层图像(T)中从金属物体(36)发出的金属假象条纹(38)。 第一处理器(40)通过应用自适应滤波器(82)来减少由温和伪影引起的条纹(38)。 过滤器(82)朝向金属物体(36)的中心垂直取向。 过滤器(82)的重量是局部结构张量和指向金属物体(36)的矢量的函数。 如果确定图像中存在强伪像,则第二处理器(48)施加正弦图完成图像算法以校正图像中的严重伪像。 正弦图完成图像和自适应滤波图像融合到最终校正图像。 在融合过程中,高度破坏的断层摄影区域被正弦图完成图像的结果所替代,其余部分由自适应滤波图像代替。
    • 7. 发明授权
    • Method to individualize kinetic parameter estimation for dynamic molecular imaging procedures
    • 对动态分子成像程序的动力学参数估计进行个性化的方法
    • US08280130B2
    • 2012-10-02
    • US12293614
    • 2007-03-19
    • Lothar SpiesManoj NarayananBart Jacob Bakker
    • Lothar SpiesManoj NarayananBart Jacob Bakker
    • G06K9/00
    • A61B5/02755G06F19/00G06T7/20G06T2207/10104G06T2207/10108G06T2207/30004G16H50/50
    • A method within dynamic molecular imaging comprising dynamically estimating a first parameter (β(x)) and a second parameter (k(x)) of an activity function describing the bio distribution of an administered tracer, is disclosed. More specifically, the method comprises specifying a first target variance (σβ,T(x)) and a second target variance (σβ,T(x)) of the first parameter (β(x)) and the second parameter (k(x)) of the activity function, respectively; initiating an image acquisition; reconstructing the first parameter (β(x)) and the second parameter (k(x)); reconstructing a first associated variance (σβ(x)) and a second associated variance (σk(x)) of the first parameter (β(x)) and the second parameter (k(x)), respectively; and repeating the image acquisition and the reconstructing until the first associated variance (σβ(x)) and the second associated variance (σk(x)) are equal to or less than the first target variance (σβ,T(x)) and the second target variance (σβ,T(x)), respectively, σβ(x)≦σβ,T(x) and σk(x)≦σβ,T(x). The method enables patient-specific adaptive protocols within molecular imaging.
    • 公开了动态分子成像中的方法,其包括动态估计描述所施用示踪物的生物分布的活动函数的第一参数(&bgr;(x))和第二参数(k(x))。 更具体地,该方法包括指定第一参数(&bgr;(x))的第一目标方差(&sgr;&bgr;,T(x))和第二目标方差(&sgr;&bgr;,T(x))和 分别为活动函数的第二个参数(k(x)); 启动图像采集; 重建第一参数(&bgr;(x))和第二参数(k(x)); 分别重建第一参数(&bgr;(x))和第二参数(k(x))的第一相关方差(&sgr;&(x))和第二相关方差(&sgr; k(x)) ; 并且重复图像获取和重建直到第一相关方差(&sgr;&bgr;(x))和第二相关方差(&sgr; k(x))等于或小于第一目标方差(&sgr;&bgr; ,T(x))和第二目标方差(&sgr;&bgr;,T(x))分别为&sgr;&bgr;(x)≦̸&sgr;&bgr; T(x)和&sgr; k(x) ≦̸&sgr;&bgr;,T(x)。 该方法使分子成像中的患者特异性自适应方案得以实现
    • 10. 发明申请
    • METHOD TO INDIVIDUALIZE KINETIC PARAMETER ESTIMATON FOR DYNAMIC MOLECULAR IMAGING PROCEDURES
    • 用于动态分子成像程序的动态参数估计方法
    • US20100232662A1
    • 2010-09-16
    • US12293614
    • 2007-03-19
    • Lothar SpiesManoj NarayananBart Jacob Bakker
    • Lothar SpiesManoj NarayananBart Jacob Bakker
    • G06K9/00
    • A61B5/02755G06F19/00G06T7/20G06T2207/10104G06T2207/10108G06T2207/30004G16H50/50
    • A method within dynamic molecular imaging comprising dynamically estimating a first parameter (β(x)) and a second parameter (k(x)) of an activity function describing the bio distribution of an administered tracer, is disclosed. More specifically, the method comprises specifying a first target variance (σβ,T(x)) and a second target variance (σβ,T(x)) of the first parameter (β(x)) and the second parameter (k(x)) of the activity function, respectively; initiating an image acquisition; reconstructing the first parameter (β(x)) and the second parameter (k(x)); reconstructing a first associated variance (σβ(x)) and a second associated variance (σk(x)) of the first parameter (β(x)) and the second parameter (k(x)), respectively; and repeating the image acquisition and the reconstructing until the first associated variance (σβ(x)) and the second associated variance (σk(x)) are equal to or less than the first target variance (σβ,T(x)) and the second target variance (σβ,T(x)), respectively, σβ(x)≦σβ,T(x) and σk(x)≦σβ,T(x). The method enables patient-specific adaptive protocols within molecular imaging.
    • 公开了动态分子成像中的方法,其包括动态估计描述所施用示踪物的生物分布的活动函数的第一参数(&bgr;(x))和第二参数(k(x))。 更具体地,该方法包括指定第一参数(&bgr;(x))的第一目标方差(&sgr;&bgr;,T(x))和第二目标方差(&sgr;&bgr;,T(x))和 分别为活动函数的第二个参数(k(x)); 启动图像采集; 重建第一参数(&bgr;(x))和第二参数(k(x)); 分别重建第一参数(&bgr;(x))和第二参数(k(x))的第一相关方差(&sgr;&(x))和第二相关方差(&sgr; k(x)) ; 并且重复图像获取和重建直到第一相关方差(&sgr;&bgr;(x))和第二相关方差(&sgr; k(x))等于或小于第一目标方差(&sgr;&bgr; ,T(x))和第二目标方差(&sgr;&bgr;,T(x))分别为&sgr;&bgr;(x)≦̸&sgr;&bgr; T(x)和&sgr; k(x) ≦̸&sgr;&bgr;,T(x)。 该方法使分子成像中的患者特异性自适应方案成为可能。