Title |
Fabrication approaches for the creation of physical models from microscopy data
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Published in |
3D Printing in Medicine, February 2017
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DOI | 10.1186/s41205-017-0011-6 |
Pubmed ID | |
Authors |
Benjamin L. Cox, Nathan Schumacher, John Konieczny, Issac Reifschneider, Thomas R. Mackie, Marisa S. Otegui, Kevin W. Eliceiri |
Abstract |
Three-dimensional (3D) printing has become a useful method of fabrication for many clinical applications. It is also a technique that is becoming increasingly accessible, as the price of the necessary tools and supplies decline. One emerging, and unreported, application for 3D printing is to aid in the visualization of 3D imaging data by creating physical models of select structures of interest. Presented here are three physical models that were fabricated from three different 3D microscopy datasets. Different methods of fabrication and imaging techniques were used in each case. Each model is presented in detail. This includes the imaging modality used to capture the raw data, the software used to create any computer models and the 3D printing tools used to create each model. Despite the differences in their creation, these examples follow a simple common workflow that is also detailed. Following these approaches, one can easily make 3D printed models from 3D microscopy datasets utilizing off the shelf commercially available software and hardware. |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 12 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Postgraduate | 2 | 17% |
Researcher | 2 | 17% |
Student > Ph. D. Student | 2 | 17% |
Other | 1 | 8% |
Student > Bachelor | 1 | 8% |
Other | 1 | 8% |
Unknown | 3 | 25% |
Readers by discipline | Count | As % |
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Engineering | 2 | 17% |
Environmental Science | 1 | 8% |
Biochemistry, Genetics and Molecular Biology | 1 | 8% |
Veterinary Science and Veterinary Medicine | 1 | 8% |
Medicine and Dentistry | 1 | 8% |
Other | 3 | 25% |
Unknown | 3 | 25% |