Automatic data-driven design and 3D printing of custom ocular prostheses

Johann Reinhard (), Philipp Urban, Stephen Bell, David Carpenter and Mandeep S. Sagoo
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Johann Reinhard: Fraunhofer Institute for Computer Graphics Research IGD
Philipp Urban: Fraunhofer Institute for Computer Graphics Research IGD
Stephen Bell: Ocupeye Ltd.
David Carpenter: Moorfields Eye Hospital NHS Foundation Trust
Mandeep S. Sagoo: NIHR Biomedical Research Centre for Ophthalmology at Moorfields Eye Hospital and UCL Institute of Ophthalmology

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract Millions of people require custom ocular prostheses due to eye loss or congenital defects. The current fully manual manufacturing processes used by highly skilled ocularists are time-consuming with varying quality. Additive manufacturing technology has the potential to simplify the manufacture of ocular prosthetics, but existing approaches just replace to various degrees craftsmanship by manual digital design and still require substantial expertise and time. Here we present an automatic digital end-to-end process for producing custom ocular prostheses that uses image data from an anterior segment optical coherence tomography device and considers both shape and appearance. Our approach uses a statistical shape model to predict, based on incomplete surface information of the eye socket, a best fitting prosthesis shape. We use a colour characterized image of the healthy fellow eye to determine and procedurally generate the prosthesis’s appearance that matches the fellow eye. The prosthesis is manufactured using a multi-material full-colour 3D printer and postprocessed to satisfy regulatory compliance. We demonstrate the effectiveness of our approach by presenting results for 10 clinic patients who received a 3D printed prosthesis. Compared to a current manual process, our approach requires five times less labour of the ocularist and produces reproducible output.

Date: 2024
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DOI: 10.1038/s41467-024-45345-5

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