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Data and figures associated with "The accuracy of 3D optical reconstruction and additive manufacturing processes in reproducing detailed subject-specific anatomy" publication

dataset
posted on 2017-10-10, 12:29 authored by Paolo Ferraiuoli, Jonathan Taylor, John FennerJohn Fenner, Andrew NarracottAndrew Narracott
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 MRI, 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 CCD cameras to provide full-field shape measurements and to generate an 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.

Ferraiuoli, P.; Taylor, J.C.; Martin, E.; Fenner, J.W.; Narracott, A.J. (2017) The Accuracy of 3D Optical Reconstruction and Additive Manufacturing Processes in Reproducing Detailed Subject-Specific Anatomy. J. Imaging, 3(4), 45. doi:10.3390/jimaging3040045

Funding

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska Curie grant agreement No 642612

History

Ethics

  • There is no personal data or any that requires ethical approval

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  • The data can be shared openly

Data description

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Methodology, headings and units

  • There is a readme.txt file describing the methodology, headings and units