ct2print voxels to mesh

A basic example of converting a voxel-based image to a simplified mesh. This interactive drag-and-drop web page allows you to create meshes that can be used with a 3D printer.

No data is sent to a server. Everything happens in your browser window, on your machine.

Usage

1. Open the live demo.
2. Option 1 The web page automatically loads with a default T1 MRI scan. If you want to use this scan, go to step 5.
3. Option 2 If your T1 MRI scan is in NIfTI format, drag and drop the file onto the web page.
4. Option 3 If your image is in DICOM format, it may load if you drag and drop the files. If this fails, convert your images with dcm2niix and save the result as a NIfTI format file that brain2print can open.
5. Note when you click on the image, the voxel intensity is shown in the status bar at the bottom-left of the web page. You can decide a nice intensity threshold to segment your image (e.g. for a CT scan, bone will be brighter than soft tissue).
6. Press the Create Mesh button and select your preferred settings:

• The Isosurface Threshold is the voxel intensity used to discriminate the mesh surface. See the previous step for detials. By default, this value is set to the Otsu threshold.
• The Hollow pull-down menu allows you to create a solid object, or a hollow one that uses less materials (but requires an escape hole).
• You can choose Smoothing to make the surfaces less jagged at the expense of computation time.
• You can choose to Simplify to reduce the number of triangles and create smaller files.

7. Once you have set your preferences, press Apply.
8. You will see the mesh appear and can interactively view it. If you are unhappy with the result, repeat step 6 with different settings. If you want to print the results, press the Save Mesh button.

For Developers

You can serve a hot-reloadable web page that allows you to interactively modify the source code.

git clone https://github.com/niivue/ct2print
cd ct2print
npm install
npm run dev

Alternatives

ct2print makes a mesh from the brightest voxels in the image. This works well for extracting the brightest tissues - for example bone from computerized axial tomography. However, if your iamge is a T1-weighted MRI scan of the head, you may prefer brain2print which uses AI methods to segment brain tissue.

References

This web page combines three packages developed by our team:

• niimath for creating hollow objects. Citation.
• niivue reading images and visualization.
• ITK-Wasm for voxel-to-mesh and mesh processing. [Citation](https://proceedings.scipy.org/articles/TCFJ5130.