Integrating statistical shape modelling into a silhouette-based 3D reconstruction process to model a transradial defect

Master Thesis (2018)
Author(s)

Steven Goes (TU Delft - Mechanical Engineering)

Contributor(s)

Dick Plettenburg – Mentor

Juan Cuellar Lopez – Mentor

Gerwin Smit – Mentor

Toon Huysmans – Mentor

Faculty
Mechanical Engineering
More Info
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Publication Year
2018
Language
English
Graduation Date
14-12-2018
Awarding Institution
Delft University of Technology
Project
Access to prosthetics thanks to 3D printing and a smartphone app
Faculty
Mechanical Engineering
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Abstract

Background: In low- and middle-income countries there is a high demand for prosthetic devices. An automatic system, in which hand prostheses are manufactured with 3D printers can potentially offer a solution for patients having a transradial defect in these areas. As part of such a system, a detailed 3D model of the residual limbs is needed. In order to make the process of creating this 3D model more accessible to low- and middle-income countries, a new silhouette-based 3D reconstruction process is observed which can be implemented in a smartphone application.
Objective:Measure the accuracy of the observed method.
Methods: A database of artificial residual limbs and an experimental algorithm is created. This algorithm consists of two parts. The first part simulates the process of capturing pictures of a residual limb with a smartphone camera. The second part performs an automatic silhouette-based 3D reconstruction.
Results: When the reconstruction method is performed on a known residual limb shape with three silhouette images, the highest measured 3D reconstruction accuracy is 1.12 ± 0.57 mm. When the method is performed on an unknown residual limb shape with three silhouette images, the highest accuracy is 6.48 ± 2.15 mm.
Conclusion:This work presents a technique for reconstructing a residual limb by means of silhouette images. The observed method can be considered as a promising 3D reconstruction approach for prosthetic designing. The method could be improved by having access to a larger database of residual limb shapes and by analysing and finding the optimal input arguments for the optimiser.

Clinical Relevance:The observed method provides a low-cost and accessible approach to model a residual limb for the design of a fitting prosthetic socket that can be manufactured by a 3D printer.

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