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. 2017 May 31;12(5):e0178540.
doi: 10.1371/journal.pone.0178540. eCollection 2017.

From medical imaging data to 3D printed anatomical models

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From medical imaging data to 3D printed anatomical models

Thore M Bücking et al. PLoS One. .

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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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. From medical image to 3D print workflow.
After the anatomical structure has been segmented (a), the resulting surface needs to be refined (b) to remove image artefacts, after which it can be 3D printed (c).
Fig 2
Fig 2. 3D printed anatomical models generated from medical imaging data using 3D Slicer and Seg3D.
Part of the ribcage (a), the liver (b), and the right lung (c).
Fig 3
Fig 3. Ribs phantom as a clinical training tool for ultrasound guided kidney biopsy.
a) 3D print of the ribs model with a chicken breast and biopsy needle b) Ultrasound scan of the model immersed in water.

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