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首页> 外文会议>Conference on image processing >Reliable Fusion of Knee Bone Laser Scans to Establish Ground Truth for Cartilage Thickness Measurement
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Reliable Fusion of Knee Bone Laser Scans to Establish Ground Truth for Cartilage Thickness Measurement

机译：可靠的膝关节骨激光扫描扫描，为软骨厚度测量建立地面真相

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We are interested in establishing ground truth data for validating morphology measurements of human knee cartilage from MR imaging. One promising approach is to compare the high-accuracy 3D laser scans of dissected cadaver knees before and after the dissolution of their cartilage. This requires an accurate and reliable method to fuse the individual laser scans from multiple views of the cadaver knees. Unfortunately existing methods using Iterative Closest Point (ICP) algorithm from off-the-shell packages often yield unreliable fusion results. We identify two major sources of variation: (i) the noise in depth measurements of the laser scans is significantly high and (ii) the use of point-to-point correspondence in ICP is not suitable due to sampling variation in the laser scans. We resolve the first problem by performing adaptive Gaussian smoothing on each individual laser scans prior to the fusion. For the second problem, we construct a surface mesh from the point cloud of each scan and adopt a point-to-mesh ICP scheme for pairwise alignment. The complete surface mesh is constructed by fusing all the scans in the order maximizing mutual overlaps. In experiments on 6 repeated scanning trials of a cadaver knee, our approach reduced the alignment error of point-to-point ICP by 30% and reduced coefficient of variation (CV) of cartilage thickness measurements from 5% down to 1.4%, significantly improving the method's repeatability.
机译：我们有兴趣建立从MR成像的验证人体膝关节软骨的形态测量的地面真实数据。一个有希望的方法是在软骨溶解之前和之后比较解剖尸体膝盖的高精度3D激光扫描。这需要准确可靠的方法来熔断各个激光扫描从尸体膝盖的多个视图。遗憾的是，使用迭代最接近点（ICP）算法的现有方法来自脱机包的算法通常会产生不可靠的融合结果。我们确定两个主要的变化来源：（i）激光扫描深度测量的噪声显着高，并且（ii）在ICP中使用点对点对应的使用由于激光扫描中的采样变化而不合适。我们通过在融合之前对每个单独的激光扫描执行自适应高斯平滑来解决第一个问题。对于第二个问题，我们从每个扫描点云构造一个表面网格，并采用用于成对对齐的点对网格ICP方案。完整的表面网格通过熔断最大化相互重叠的顺序中的所有扫描来构造。在实验中，在尸体膝关节的6重复扫描试验中，我们的方法将点对点ICP的对准误差减少30％，并且软骨厚度测量的变异系数降低（CV）从5％降至1.4％，显着改善该方法的重复性。

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