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A 3D Slicer Extension for fabrication of physical objects

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Introduction

This extension for 3D Slicer creates a full-color image stack suitable for bitmap-based multimaterial 3D printing. In contrast to traditional 3D printing methods, this new technique does not require image segmentation (which is a difficult and labor-intensive processing step) and produces highly detailed physical models.

Example printed models

More info:

  • Hosny et al., "From Improved Diagnostics to Presurgical Planning: High-Resolution Functionally Graded Multimaterial 3D Printing of Biomedical Tomographic Data Sets", 3D Printing and Additive Manufacturing VOL. 5, NO. 2, 2018 reference / full text
  • Article in Science Daily
  • Discussion

Caveats

Please note:

  • this process is only compatible with a limited range of newer printers and not traditional filament-based printers. See the paper for more detail about the printers for which ths approach has been used.
  • the developers of SlicerFab are affiliated with any printer company so we don't know the details about what printers may or may not support SlicerFab now or in the future.
  • some of the steps in this printing process require custom python coding to convert the generated bitmaps into files compatible with particular printers.
  • we hope to provide more details on workflows that are known to generate prints as we gain experience with compatible printers.

This is meant to be a community effort - if you have experience with this kind of printers please share!

Process

Turns this: rendering.png

Into this: slices.png

Usage

  1. Install a recent nightly version of 3D Slicer
  2. Start Slicer, open Extension Manager, and install SlicerFab extension
  3. Load data and set up Volume Rendering (see docs and examples at slicer.org
  4. Select the BitmapGenerator module
  5. Set the output path (/tmp by default, for windows change to c:/TEMP or something)
  6. Click Apply and let the slices get generated.

Any questions? Post it on SlicerFab discussion in Slicer forum

Work in Progress - Please use with caution and add improvements if you can.

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  • Python 70.7%
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