Bucking, TM;
Hill, ER;
Robertson, JL;
Maneas, E;
Plumb, AA;
Nikitichev, DI;
(2017)
From medical imaging data to 3D printed anatomical models.
PLoS ONE
, 12
(5)
, Article e0178540. 10.1371/journal.pone.0178540.
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Abstract
Anatomical models are important training and teaching tools in the clinical environment and are routinely used in medical imaging research. Advances in segmentation algorithms and increased availability of three-dimensional (3D) printers have made it possible to create cost-efficient patient-specific models without expert knowledge. We introduce a general workflow that can be used to convert volumetric medical imaging data (as generated by Computer Tomography (CT)) to 3D printed physical models. This process is broken up into three steps: image segmentation, mesh refinement and 3D printing. To lower the barrier to entry and provide the best options when aiming to 3D print an anatomical model from medical images, we provide an overview of relevant free and open-source image segmentation tools as well as 3D printing technologies. We demonstrate the utility of this streamlined workflow by creating models of ribs, liver, and lung using a Fused Deposition Modelling 3D printer.
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