IEEE Access (Jan 2018)

Automatic Design and Fabrication of a Custom Ocular Prosthesis Using 3D Volume Difference Reconstruction (VDR)

  • Xin Ye,
  • Shaoze Wang,
  • Yan Zhu,
  • Huifeng Shao,
  • Lixia Lou,
  • Dahong Qian,
  • Juan Ye

DOI
https://doi.org/10.1109/ACCESS.2018.2802700
Journal volume & issue
Vol. 6
pp. 14339 – 14346

Abstract

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We have developed a new computed tomography (CT)-based 3-D volume difference reconstruction (VDR) method for building a model of soft tissue differences using facial self-referenced prototyping computation, and a computer-aided design (CAD) workflow for fabricating custom ocular prostheses (COPs). In facial self-referenced prototyping computation, an ocular prosthesis is constructed from a combination of a top surface, shape contour, and bottom surface, with key measurements being made with respect to the patient's healthy eye. The top surface is derived from the outer region of the healthy eyeball, using Hough transformation. In the meantime, the shape contour and bottom surface are computed from facial edges fitted to Fourier curves. Once these self-referenced parameters have been obtained, finite element analysis is used to generate a primitive prosthesis model. Before being converted into a format suitable for rapid prototyping techniques, the model is refined using surface equations. Oculists choose the final optimized model for printing. Geometric errors, compared with a manually-fabricated prosthesis which has gone through multiple rounds of time-consuming manual adjustment, are as low as 0.46%, and the fabrication time and human error have been greatly reduced. The fill density of the COP is 60%, the wall thickness is 1.6 mm and the weight is 1.59 g. The reconstructed contours and symmetry of the COP are satisfactory with doctors' evaluation and the patient is able to have a normal appearance. The CT-based VDR method we first proposed here can accurately build a model of the soft tissue difference. The full CAD workflow has improved prosthesis design and manufacturing efficiency. This flow can also be applied to other soft issue reconstruction.

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