Statistical and Metrological Framework for Evaluation of micro-CT 3D Data with Application to Dental Implant Components

Dimensional comparison of micro-computed tomography (micro-CT) reconstructions with CAD geometry requires a precise definition of the evaluated surface points. We apply a statistical and metrological framework to signed CAD–CT deviations at the vertices of three geometrically different titanium dental implant components, D1–D3, representing complex surface geometry, substantial μCT-to-CAD deviations, and ambiguous initial alignment. Complete exports contain 75 812, 46 954, and 16 416 measured-surface vertices. The corresponding RMS deviations are 49.14 μm, 207.72 μm, and 77.07 μm. Empirical cumulative distribution functions, histograms normalized to unit area, and descriptive summaries compare the observed meshes; two-sample Kolmogorov–Smirnov (KS) distances quantify differences between their vertex distributions. D2 has the largest absolute-deviation upper tail. A detailed axial analysis of D1 localizes all 267 vertices with absolute deviation above 200 μm in one of 12 intervals. Separate area-sampled and radial D1 exports provide sensitivity checks for alternative surface and correspondence definitions. Because vertices are spatially dependent and mesh density determines their weighting, conventional KS p-values are only nominal reference calculations. A prospective observation model distinguishes physical deviation from measurement and alignment effects. The workflow provides a reproducible basis for statistical evaluation and measurement-uncertainty assessment of individual components.