An automated parametric ear model to improve frugal 3D scanning methods for the advanced manufacturing of high-quality prosthetic ears

Abstract

Ear prostheses are commonly used for restoring aesthetics to those suffering missing or malformed external ears. Traditional fabrication of these prostheses is labour intensive and requires expert skill from a prosthetist. Advanced manufacturing including 3D scanning, modelling and 3D printing has the potential to improve this process, although more work is required before it is ready for routine clinical use. In this paper, we introduce a parametric modelling technique capable of producing high quality 3D models of the human ear from low-fidelity, frugal, patient scans; significantly reducing time, complexity and cost. Our ear model can be tuned to fit the frugal low-fidelity 3D scan through; (a) manual tuning, or (b) our automated particle filter approach. This potentially enables low-cost smartphone photogrammetry-based 3D scanning for high quality personalised 3D printed ear prosthesis. In comparison to standard photogrammetry, our parametric model improves completeness, from (81 ± 5)% to (87 ± 4)%, with only a modest reduction in accuracy, with root mean square error (RMSE) increasing from (1.0 ± 0.2) mm to (1.5 ± 0.2) mm (relative to metrology rated reference 3D scans, n = 14). Despite this reduction in the RMS accuracy, our parametric model improves the overall quality, realism, and smoothness. Our automated particle filter method differs only modestly compared to manual adjustments. Overall, our parametric ear model can significantly improve quality, smoothness and completeness of 3D models produced from 30-photograph photogrammetry. This enables frugal high-quality 3D ear models to be produced for use in the advanced manufacturing of ear prostheses.