Geometric and Visual Quality of Photogrammetry Models for Anatomical Research: A Multi-Method Validation on Dissected Body Donor Material

Purpose Photogrammetry models allow for measurements to be taken in three dimensions. However, to use these models in research, they must be both visually realistic and dimensionally accurate. Validation studies have primarily focused on dry skeletal material. The purpose of this study was to evaluate the geometric accuracy and visual quality of photogrammetry-derived 3D models of dissected human donor tissue using computed tomography as a reference, and to assess the impact of lighting conditions, capture devices, and reconstruction platforms. Methods Two embalmed dissected cervical spines were photographed using a digital single-lens reflex camera with diffuse and cross-polarized lighting, and a smartphone with diffuse lighting. Models were reconstructed using two free photogrammetry platforms (Apple’s Object Capture and Epic Games’ RealityScan). Geometric accuracy was quantified by aligning the models to a high-resolution computed tomography scan and measuring surface deviations. Visual quality was evaluated by six anatomical researchers using a visual analog scale. Results All configurations achieved sub-millimeter geometric accuracy relative to CT, with mean surface deviations <0.1 mm and precision ranging from 0.25 to 0.30 mm. Reconstruction software influenced mesh density but not overall geometric fidelity. Diffuse lighting with the professional camera yielded the highest visual quality scores. Cross-polarization did not significantly improve geometric accuracy over diffuse lighting. Smartphone-based acquisition produced geometric and visual results remarkably close to the professional setup. Conclusion Modern accessible photogrammetry pipelines can reconstruct dissected soft tissue with exceptional geometric fidelity and high visual realism, providing a robust and cost-effective method for 3D morphometric analysis in anatomical research.