From medical imaging data to 3D printed anatomical models.
Thore M Bücking1, Emma R Hill1, James L Robertson1
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.
Plos One
|June 1, 2017
Summary
This study presents a streamlined workflow for creating patient-specific anatomical models from medical imaging data using 3D printing. The process utilizes free software and accessible technologies for cost-efficient model generation.
Area of Science:
- Medical Imaging and 3D Printing
- Biomedical Engineering
- Anatomical Modeling
Background:
- Anatomical models are crucial for clinical training, teaching, and medical imaging research.
- Recent advancements in segmentation algorithms and 3D printing have enabled accessible creation of patient-specific models.
Purpose of the Study:
- To introduce a general workflow for converting volumetric medical imaging data into 3D printed anatomical models.
- To provide an overview of free, open-source image segmentation tools and 3D printing technologies.
- To lower the barrier to entry for creating cost-efficient, patient-specific anatomical models.
Main Methods:
- A three-step process: image segmentation, mesh refinement, and 3D printing.
- Utilized Computer Tomography (CT) data for model generation.
- Demonstrated the workflow using Fused Deposition Modelling (FDM) 3D printing technology.
Main Results:
- Successfully created patient-specific 3D printed models of ribs, liver, and lung.
- The workflow is streamlined and does not require expert knowledge.
- Cost-efficient model creation is achievable with readily available tools and technologies.
Conclusions:
- The presented workflow effectively converts medical imaging data into physical anatomical models.
- This approach democratizes the creation of patient-specific models for various applications.
- The study highlights the utility of open-source software and accessible 3D printing for anatomical model generation.
