A Slicer-Independent Framework for Measuring G-Code Accuracy in Medical 3D Printing

In medical 3D printing, accuracy is critical for fabricating patient-specific implants and anatomical models. Although printer performance has been widely examined, the influence of slicing software on geometric fidelity is less frequently quantified. The slicing step, which converts STL files into printer-readable G-code, may introduce deviations that affect the final printed object. To quantify slicer-induced G-code deviations by comparing G-code-derived geometries with their reference STL modelsTwenty mandibular models were processed using five slicers (PrusaSlicer (version 2.9.1.), Cura (version 5.2.2.), Simplify3D (version 4.1.2.), Slic3r (version 1.3.0.) and Fusion 360 (version 2.0.19725)). A custom Python workflow converted the G-code into point clouds and reconstructed STL meshes through XY and Z corrections, marching cubes surface extraction, and volumetric extrusion. A calibration object enabled coordinate normalization across slicers. Accuracy was assessed using Mean Surface Distance (MSD), Root Mean Square (RMS) deviation, and Volume Difference. MSD ranged from 0.071 to 0.095 mm, and RMS deviation from 0.084 to 0.113 mm, depending on the slicer. Volumetric differences were slicer-dependent. PrusaSlicer yielded the highest surface accuracy; Simplify3D and Slic3r showed best repeatability. Fusion 360 produced the largest deviations. The slicers introduced geometric deviations below 0.1 mm that represent a substantial proportion of the overall error in the FDM workflow.