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    • 1. 发明申请
    • CORRECTION OF BOUNDARY ARTEFACTS IN IMAGE DATA PROCESSING
    • 边界条件在图像数据处理中的校正
    • WO2002084594A2
    • 2002-10-24
    • PCT/GB2002/000768
    • 2002-02-21
    • VOXAR LIMITEDPAPAGEORGIOU, PavlosPOOLE, Ian
    • PAPAGEORGIOU, PavlosPOOLE, Ian
    • G06T5/30
    • G06T5/30G06T2207/10081G06T2207/10088G06T2207/10104
    • An image processing system is described in which sets of image elements having display values outside of a target range B of display values are each respectively morphologically dilated. The intersection between the morphologically dilated sets of image elements is then identified and those image elements within the intersecting region are removed from the set of image elements having the target range B of display values. This removes image elements incorrectly appearing to have display values corresponding to the target range B of display values due to aliasing effect between regions of image elements having display values either side of the target range B of imaging may be two-dimensional or three-dimensional imaging. The morphologically dilatation is preferably performed with a quasi-circular or a quasi-spherical structuring element having a radius of between two and three voxels.
    • 描述了一种图像处理系统,其中分别在显示值的目标范围B之外的显示值的图像元素组分别形态地扩大。 然后识别形态扩张的图像元素集合之间的交集,并且从具有显示值的目标范围B的图像元素集合中去除交叉区域内的那些图像元素。 这样除去由于具有显示值的图像元素的区域之间的混叠效应而与显示值的目标范围B相对应的显示值不正确地出现的图像元素可以是二维或三维成像 。 形态学上的扩张优选用具有半径在二和三个体素之间的准圆形或准球形结构元件进行。
    • 5. 发明申请
    • METHOD FOR DETERMINING A PATH ALONG A BIOLOGICAL OBJECT WITH A LUMEN
    • 用于确定生物对象与路灯的方法
    • WO2007015061A1
    • 2007-02-08
    • PCT/GB2006/002740
    • 2006-07-20
    • BARCO NVPOOLE, Ian
    • POOLE, Ian
    • G06T5/00
    • G06T7/60G06T7/12G06T7/181G06T2207/10072G06T2207/20101G06T2207/30101
    • A path between specified start and end voxels along a biological object with a lumen, such as a vessel, within a patient image three-dimensional volume data set comprising an array of voxels of varying value is identified using an algorithm that works outwards from the start voxel to identify paths of low cost via intermediate voxels. The intermediate voxels are queued for further expansion of the path using a priority function comprising the sum of the cost of the path already found from the start voxel to the intermediate voxel and the Euclidean distance from the intermediate voxel to the end voxel. A cost function that depends on the voxel density is used to bias the algorithm towards paths inside the object. The number of iterations of the voxel required to find a path from the start to the end voxel, and hence the time taken, can be significantly reduced by scaling the Euclidean distance by a constant. Usefully, the constant is greater than 1, such as between 1.5 and 2.
    • 使用从开始向外工作的算法来识别包括具有变化值的体素阵列的患者图像三维体数据集内的具有管腔(例如血管)的生物体的指定起始和终止体素之间的路径 体素通过中间体素识别低成本的路径。 使用包括已经从起始体素到中间体素已经发现的路径的总和的总和的优先级函数以及从中间体素到终体体素的欧几里德距离来排列中间体素用于路径的进一步扩展。 使用取决于体素密度的成本函数将算法偏向对象内的路径。 通过将欧几里德距离缩放常数,可以显着减少从开始到结束体素找到路径所需的体素的迭代次数以及所花费的时间。 有用地,常数大于1,例如在1.5和2之间。