Bücking Thore M, Hill Emma R, Robertson James L, Maneas Efthymios, Plumb Andrew A, Nikitichev Daniil I
Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.
Centre for Medical Imaging, University College London, London, United Kingdom.
PLoS One. 2017 May 31;12(5):e0178540. doi: 10.1371/journal.pone.0178540. eCollection 2017.
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.
解剖模型是临床环境中重要的培训和教学工具,并且在医学影像研究中经常被使用。分割算法的进步以及三维(3D)打印机可用性的提高使得无需专业知识就能创建具有成本效益的患者特异性模型成为可能。我们介绍一种通用工作流程,可用于将体积医学影像数据(如计算机断层扫描(CT)生成的数据)转换为3D打印实体模型。这个过程分为三个步骤:图像分割、网格细化和3D打印。为了降低入门门槛,并在旨在从医学图像3D打印解剖模型时提供最佳选择,我们概述了相关的免费和开源图像分割工具以及3D打印技术。我们通过使用熔融沉积建模3D打印机创建肋骨、肝脏和肺部模型来展示这种简化工作流程的实用性。