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    • 3. 发明授权
    • Fluoroscopy based 3-D neural navigation based on 3-D angiography reconstruction data
    • 基于3-D血管造影重建数据的基于荧光透视的3-D神经导航
    • US06389104B1
    • 2002-05-14
    • US09607906
    • 2000-06-30
    • Ali Bani-HashemiArun KrishnanJames Williams
    • Ali Bani-HashemiArun KrishnanJames Williams
    • A61B603
    • A61B6/504A61B6/12A61B6/4441A61B6/463A61B6/466A61B6/481A61B6/5235A61B6/5247A61B90/36G06T11/006G06T2211/404G06T2211/412G06T2211/428
    • A method and apparatus for providing a high-quality representation of a volume having a real-time 3-D reconstruction therein of movement of an object, wherein the real-time movement of the object is determined using a lower-quality representation of only a portion of the volume. Movement of the object is detected in a 2-D X-ray fluoroscopy image and is reconstructed in a 3-D angiography (X-ray) reconstruction. Using a common C-arm and X-ray geometry advantageously, the 2-D and 3-D data representative of vascular structures of a patient is acquired, thereby facilitating the merger of the real-time 2-D fluoroscopic images with the 3-D reconstructed vascular structures in a common 3-D-visualization framework. Also described is a technique for 3-D reconstruction of a catheter from real-time 2-D fluoroscopic images and stored 3-D angiography data, so as to present the 3-D reconstructed catheter in the common coordinate frame. The merger of 3-D angiography image representations acquired with other modalities, such as MR or CT, is also disclosed.
    • 一种用于提供其中具有物体的移动的实时3维重建的体积的高质量表示的方法和装置,其中使用较低质量的仅仅一个 部分音量。 在2-D X射线荧光透视图像中检测物体的移动,并在3-D血管造影(X射线)重建中重建。 有利地使用常见的C形臂和X射线几何形状,代表患者的血管结构的2-D和3-D数据,从而有助于将实时2-D透视图像与3- D重建血管结构在一个共同的3-D可视化框架。 还描述了一种用于从实时二维透视图像和存储的三维血管造影数据进行导管三维重建的技术,以将3-D重建的导管呈现在共同的坐标系中。 还公开了与其他方式(例如MR或CT)获得的3-D血管造影图像表示的合并。
    • 5. 发明授权
    • System and method for in-context volume visualization using virtual incision
    • 使用虚拟切口进行上下文卷可视化的系统和方法
    • US08466916B2
    • 2013-06-18
    • US11675135
    • 2007-02-15
    • Klaus EngelJames Williams
    • Klaus EngelJames Williams
    • G06T17/00
    • G06T15/08
    • A method for volume rendering a digitized medical image includes providing a digitized medical image volume comprising a plurality of intensities on a 3-dimensional grid of points, providing a projection plane comprising a 2-dimensional lattice of points onto which rendering rays are projected from a viewing point through the image volume, advancing a sampling point along a ray through the image volume, generating an incision region within the image volume, determining whether the sampling point is within the incision region, where a first transfer function is applied to a sample value interpolated from a first volume if the sampling point is within the incision region, and a second transfer function is applied to a sample value interpolated from a second volume if the sampling point is outside the incision region, and accumulating the output of the transfer function.
    • 用于体绘制数字化医学图像的方法包括在三维网格网格上提供包括多个强度的数字化医学图像体积,提供投影平面,该投影平面包括从其上投影渲染光线的点的二维点阵 通过图像体积观察点,沿着光线推进采样点通过图像体积,在图像体积内产生切割区域,确定采样点是否在切口区域内,其中第一传递函数被应用于样本值 如果采样点在切口区域内,则从第一卷内插,并且如果采样点在切口区域之外,则将第二传递函数应用于从第二卷内插的采样值,并累加传递函数的输出。
    • 9. 发明申请
    • AUTOMATIC ORGAN DETECTION USING MACHINE LEARNING AND CLASSIFICATION ALGORITHMS
    • 使用机器学习和分类算法的自动机器检测
    • US20080154565A1
    • 2008-06-26
    • US11747961
    • 2007-05-14
    • Charles FlorinJames Williams
    • Charles FlorinJames Williams
    • G06G7/60
    • G06K9/6256G06K2209/05G06T7/70G06T2207/10072G06T2207/30092
    • A method and apparatus of visually depicting an organ, having the steps of choosing a predefined set features for analysis, the predefined set of features having distinguishing weak learners for an algorithm, wherein the predefined set of features and the weak learners chosen distinguish features of the organ desired to be represented, developing a strong classifier for the algorithm for the organ desired to be represented based upon the weak learners for the organ, one of conducing a body scan to produce a body scan data set and obtaining a body scan data set of information for a patient, applying the strong classifier and the algorithm to the body scan data set to develop a result of a representation of the organ and outputting the result of the step of applying of the strong classifier and the algorithm to the body scan data set to represent the organ.
    • 一种视觉描绘器官的方法和装置,具有选择用于分析的预定义集合特征的步骤,所述预定义特征集合具有针对算法的区别弱学习者,其中所选择的特定组和弱学习者选择区分特征的特征 期望被表示的器官,为基于用于器官的弱学习者所希望表示的器官的算法开发强分类器,其中一个是进行身体扫描以产生身体扫描数据集并且获得身体扫描数据集 用于患者的信息,将强分类器和算法应用于身体扫描数据集以产生器官表示的结果,并将强分类器和算法的步骤的结果输出到身体扫描数据集 代表器官。
    • 10. 发明申请
    • SYSTEM AND METHOD FOR IN-CONTEXT MPR VISUALIZATION USING VIRTUAL INCISION VOLUME VISUALIZATION
    • 使用虚拟入侵体视觉化的内在MPR可视化的系统和方法
    • US20070229500A1
    • 2007-10-04
    • US11684685
    • 2007-03-12
    • Klaus EngelJames Williams
    • Klaus EngelJames Williams
    • G06T17/00
    • G06T19/00G06T15/08G06T2219/008Y10T428/24355Y10T428/25
    • A method for multi-planar reconstruction of digitized medical images includes providing an image volume, sampling the neighborhood about each point in a planar region and saving a color value and a depth, providing a projection plane onto which rendering rays are projected from a viewing point through said image volume, advancing sampling points along rays through the image volume, computing depths of each sampling point, determining for sampling points on rays that penetrates the planar region if a depth of said sampling point is less than the buffer depth of a corresponding point in the planar region and sampling neighborhoods of points about such sampling points, determining if sampling points are near said planar region, applying first transfer function to sample values interpolated from first volume for sampling points close to or inside the planar region, and otherwise applying second transfer function to sample values interpolated from second volume.
    • 一种用于数字化医学图像的多平面重构的方法包括提供图像体积,对平面区域中的每个点进行邻域采样,并且保存颜色值和深度,从而提供投影平面,在该投影平面上,从观察点 通过所述图像体积,沿着光线通过图像体积推进采样点,计算每个采样点的深度,如果所述采样点的深度小于对应点的缓冲器深度,则确定穿透平面区域的射线上的采样点 在平面区域中,并且对这些采样点的点的采样邻域,确定采样点是否靠近所述平面区域,将第一传递函数应用于从接近或在平面区域内的采样点从第一体积内插的采样值, 传递函数到从第二卷插值的样本值。