In this paper, the authors propose a novel method whereby a prescribed simulated skin graft is 3D printed, followed by the realization of a 3D model representation using an open-source software AutoDesk 123D Catch to reconstruct the entire simulated skin area. The methodology is photogrammetry, which measures the 3D model of a real-word object. Specifically, the principal algorithm of the photogrammetry is structure from motion (SfM) which provides a technique to reconstruct a 3D scene from a set of images collected using a digital camera. This is an efficient approach to reconstruct the burn depth compared to other non-intrusive 3D optical imaging modalities (laser scanning, optical coherence tomography). Initially, an artificial human hand with representative dimensions is designed using a CAD design program. Grooves with a step-like depth pattern are then incorporated into the design in order to simulate a skin burn wound depth map. Then, the *.stl format file of the virtually wounded artificial hand is extruded as a thermoplastic material, acrylonitrile butadiene styrene (ABS), using a commercial 3D printer. Next, images of the grooves representing different extents of burned injury are acquired by a digital camera from different directions with respect to the artificial hand. The images stored in a computer are then imported into AutoDesk 123D Catch to process the images, thereby yielding the 3D surface model of the simulated hand with a burn wound depth map. The output of the image processing is a 3D model file that represents the groove on the plastic object and thus the burned tissue area. One dimensional sliced sections of the designed model and reconstructed model are compared to evaluate the accuracy of the reconstruction methodology. Finally, the 3D CAD model is designed with a prescribed internal tissue scaffold structure and sent to the dedicated software of the 3D printing system to print the design of the virtual skin graft with biocompatible material poly-ε-caprolactone (PCL).

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