In summer 2016, I completed a project on 3D printing which contributed to the following publication. Follow the link below for the full text.
J. Imaging 2017, 3(4), 45; https://doi.org/10.3390/jimaging3040045
by Paolo Ferraiuoli, Jonathan C. Taylor, Emily Martin, John W. Fenner and Andrew J. Narracott
Received: 31 August 2017 / Accepted: 6 October 2017 / Published: 12 October 2017
3D reconstruction and 3D printing of subject-specific anatomy is a promising technology for supporting clinicians in the visualisation of disease progression and planning for surgical intervention. In this context, the 3D model is typically obtained from segmentation of magnetic resonance imaging (MRI), computed tomography (CT) or echocardiography images. Although these modalities allow imaging of the tissues in vivo, assessment of quality of the reconstruction is limited by the lack of a reference geometry as the subject-specific anatomy is unknown prior to image acquisition. In this work, an optical method based on 3D digital image correlation (3D-DIC) techniques is used to reconstruct the shape of the surface of an ex vivo porcine heart. This technique requires two digital charge-coupled devices (CCD) cameras to provide full-field shape measurements and to generate a standard tessellation language (STL) file of the sample surface. The aim of this work was to quantify the error of 3D-DIC shape measurements using the additive manufacturing process. The limitations of 3D printed object resolution, the discrepancy in reconstruction of the surface of cardiac soft tissue and a 3D printed model of the same surface were evaluated. The results obtained demonstrated the ability of the 3D-DIC technique to reconstruct localised and detailed features on the cardiac surface with sub-millimeter accuracy.
Keywords: 3D reconstruction; digital image correlation (DIC); geometric discrepancies; additive manufacturing; soft tissues; shape measurements