Anatomically accurate models can be computer-generated from medical image data. Imaging phantoms are also important for the development of novel imaging modalities such as photoacoustics, or for validation of imagebased biomarkers such as pore size estimation using nuclear magnetic resonance, where they provide controlled experimental environments. Lastly, anatomical phantoms can be designed to mimic tissue when imaged with the modality of interest most commonly ultrasound, Computed Tomography (CT), or Magnetic Resonance Imaging (MRI). In addition, the phantoms can be used for pre-operative surgical planning, which has been shown to be beneficial in craniofacial surgery and is being explored in a number of other surgical fields.
For example, improvement of central venous catheter insertions has been achieved by the use of anatomically and ultrasonically accurate teaching phantoms. Simulation-based training with anatomical models reduces the risks of surgical interventions, which are directly linked to patient experience and healthcare costs. In the clinic, the physical interaction with models facilitates learning anatomy and how different structures interact spatially in the body. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Īnatomical models have applications in clinical training and surgical planning as well as in medical imaging research. Received: OctoAccepted: Published: May 31, 2017Ĭopyright: © 2017 Bu¨cking et al. 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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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. This process is broken up into three steps: image segmentation, mesh refinement and 3D printing. 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. Advances in segmentation algorithms and increased availability of three-dimensional (3D) printers have made it possible to create costefficient patient-specific models without expert knowledge. org/10.1371/journal.pone.0178540 Editor: Han-Chiao Isaac Chen, University of Pennsylvania, UNITED STATESĪbstract Anatomical models are important training and teaching tools in the clinical environment and are routinely used in medical imaging research. OPEN ACCESS Citation: Bu¨cking TM, Hill ER, Robertson JL, Maneas E, Plumb AA, Nikitichev DI (2017) From medical imaging data to 3D printed anatomical models. Nikitichev1 1 Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 2 Centre for Medical Imaging, University College London, London, United Kingdom * Ī1111111111 a1111111111 a1111111111 a1111111111 a1111111111
From medical imaging data to 3D printed anatomical models Thore M.
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