METHOD FOR OPERATING AN X-RAY DIAGNOSTIC APPARATUS FOR DETERMINING QUALITY VALUES
    4.
    发明申请
    METHOD FOR OPERATING AN X-RAY DIAGNOSTIC APPARATUS FOR DETERMINING QUALITY VALUES 有权
    用于确定质量值的X射线诊断装置的方法

    公开(公告)号:US20090169088A1

    公开(公告)日:2009-07-02

    申请号:US12401295

    申请日:2009-03-10

    IPC分类号: G06K9/00

    摘要: A method for checking an x-ray diagnostic apparatus is provided. Fluoroscopic series of x-ray images of a technical phantom are digitally acquired and stored. Difference between a dynamic image and a background image is calculated. A measuring field is predicted. Priori information about the shape of a clinically relevant object is determined. Hough transformation on a gray value image corresponding to the difference is applied. Contrast of the object from the Hough-transformed gray value image is determined. A square of the determined contrast is calculated. A noise variance is calculated by determining a sum of a noise variance of a homogenous image region and a variance of the background image. A contrast-to-noise ratio of the determined contrast and the calculated noise variance is determined. A square of the contrast-to-noise ratio is dynamically averaged. A Clinical Relevant Fluoroscopy Performance index for the x-ray diagnostic apparatus is determined.

    摘要翻译: 提供了一种用于检查x射线诊断装置的方法。 数字获取和存储技术幻像的荧光系列X射线图像。 计算动态图像和背景图像之间的差异。 预测测量场。 确定关于临床相关对象的形状的优先信息。 应用与差异对应的灰度值图像上的霍夫变换。 确定来自霍夫变换灰度值图像的对象的对比度。 计算确定的对比度的平方。 通过确定均匀图像区域的噪声方差和背景图像的方差的和来计算噪声方差。 确定所确定的对比度和所计算的噪声方差的对比噪声比。 动态平均对比噪声比的平方。 确定X线诊断仪的临床相关荧光检查性能指标。

    Method and system for correcting butting artifacts in X-ray images
    5.
    发明申请
    Method and system for correcting butting artifacts in X-ray images 有权
    用于校正X射线图像中的伪像的方法和系统

    公开(公告)号:US20090080756A1

    公开(公告)日:2009-03-26

    申请号:US12283357

    申请日:2008-09-11

    IPC分类号: G06K9/00

    摘要: A method and system for correcting butting artifacts in x-ray images is disclosed. In order to correct a butting artifact in an x-ray image, a butting artifact region in the x-ray image is normalized. Multiple intensity shift estimators are calculated for each pixel of each line of the butting artifact. Confidence intervals are calculated for each intensity shift estimator. A multiple hypothesis hidden Markov model (MH-HMM) is formulated based on the intensity shift operators and confidence measures subject to a smoothness constraint, and the MH-HMM is solved to determine intensity shift values for each pixel. A corrected image is generated by adjusting the intensity of each pixel of the butting artifact based on the intensity shift value for that pixel.

    摘要翻译: 公开了一种用于校正X射线图像中的伪像的方法和系统。 为了校正X射线图像中的对接伪影,对x射线图像中的对接伪影区域进行归一化。 针对对接工件的每一行的每个像素计算多个强度偏移估计量。 为每个强度偏移估计器计算置信区间。 基于强度偏移算子和基于平滑度约束的置信度度度,制定了多重假设隐马尔可夫模型(MH-HMM),并求解了MH-HMM,以确定每个像素的强度偏移值。 通过基于该像素的强度偏移值调整对接伪影的每个像素的强度来生成校正图像。

    Method and system for correcting butting artifacts in X-ray images
    9.
    发明授权
    Method and system for correcting butting artifacts in X-ray images 有权
    用于校正X射线图像中的伪像的方法和系统

    公开(公告)号:US08073191B2

    公开(公告)日:2011-12-06

    申请号:US12283357

    申请日:2008-09-11

    IPC分类号: G06K9/00

    摘要: A method and system for correcting butting artifacts in x-ray images is disclosed. In order to correct a butting artifact in an x-ray image, a butting artifact region in the x-ray image is normalized. Multiple intensity shift estimators are calculated for each pixel of each line of the butting artifact. Confidence intervals are calculated for each intensity shift estimator. A multiple hypothesis hidden Markov model (MH-HMM) is formulated based on the intensity shift operators and confidence measures subject to a smoothness constraint, and the MH-HMM is solved to determine intensity shift values for each pixel. A corrected image is generated by adjusting the intensity of each pixel of the butting artifact based on the intensity shift value for that pixel.

    摘要翻译: 公开了一种用于校正X射线图像中的伪像的方法和系统。 为了校正X射线图像中的对接伪影,对x射线图像中的对接伪影区域进行归一化。 针对对接工件的每一行的每个像素计算多个强度偏移估计量。 为每个强度偏移估计器计算置信区间。 基于强度偏移算子和基于平滑度约束的置信度度度,制定了多重假设隐马尔可夫模型(MH-HMM),并求解了MH-HMM,以确定每个像素的强度偏移值。 通过基于该像素的强度偏移值调整对接伪影的每个像素的强度来生成校正图像。