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A Docker image for painlessly converting head MRI data to a 3D surface model of the brain.

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mri2stl

A Docker image for painlessly converting head MRI data to a 3D surface model of the brain.

Modified from miykael/3dprintyourbrain

Motivations

I had a head study done, and because I was the curious type, my doctor informed me I could get my medical records for free on a CD. So I naturally did so immediately after the study, and then I started my journey to create a 3D model of my brain from many black and white medical images. This has been done well before, but it was still a headache to set up. ;) Also, non-Linux users are left out in the rain, that is unless they want to setup a VM, install a Linux distro, then finally go through the awful setup. There had to be a better way.

Enter Docker! It's sort of like a VM, but it runs way faster, and doesn't take any time to set up. Just download and run, like you might do with a cross-platform Java (.jar) file. It creates a virtual computer environment that has the OS and all the files + installed programs that you need for your program! This is my Docker "image" with everything you need already set up for turning DICOM/NIfTI image sets into an .stl 3D model, ready for printing or other uses. You can do this with only one dead-simple command! You use it through your browser, through something very cool called a Jypyter notebook.

Installing and Running

To run the Docker image:

  • Install Docker on your computer
  • Run the command docker run --rm -it -p 8888:8888 nimaid/mri2stl
  • Go to 127.0.0.1:8888 in your web browser
Detailed Instructions for Beginners

Install Docker

Install Docker for your platform. This will literally be the only hard step of the whole process, and it's different for each OS. You can learn more here, and through Google. Don't panic! It's still pretty easy, especially on Windows.

Start the server

When you try to run an image in Docker, it will automatically download the latest version of that image if it's not already on your local computer. You can run the server as follows:

launch.bash (Linux) or launch.bat (Win)

This runs the image in the foreground, so that closing the command window or pressing CTRL-C kills server. This is equivalent to the command docker run --rm -it -p 8888:8888 nimaid/mri2stl

Be aware that killing the server immediately and permanently erases all data you may have uploaded or created. Please be careful and save your work before killing the server.

NOTE: If you want to run the image in the background (advanced), use the command docker run --rm -p 8888:8888 nimaid/mri2stl. You will have to manually kill the server, either through the GUI or through docker commands.

After Docker downloads the latest image, the server will start running and you should see something like the following:

[I 22:39:57.565 NotebookApp] Writing notebook server cookie secret to /root/.local/share/jupyter/runtime/notebook_cookie_secret
[I 22:39:57.728 NotebookApp] Serving notebooks from local directory: /3dprintscript
[I 22:39:57.728 NotebookApp] The Jupyter Notebook is running at:
[I 22:39:57.729 NotebookApp] http://(0d0e3db6f247 or 127.0.0.1):8888/?token=b9596f04a97c1ae9c2b02dd1877568f5ea20c805aa1199fa
[I 22:39:57.729 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 22:39:57.734 NotebookApp]

    To access the notebook, open this file in a browser:
        file:///root/.local/share/jupyter/runtime/nbserver-6-open.html
    Or copy and paste one of these URLs:
        http://(0d0e3db6f247 or 127.0.0.1):8888/?token=b9596f04a97c1ae9c2b02dd1877568f5ea20c805aa1199fa

Go to the Server's Website

You can now minimize (not close) the command line window. In your browser, navigate to the URL 127.0.0.1:8888. You should see it load a website.

Making the actual 3D model

Now you will need to select the scan to upload. When you get an MRI study done, they usually take several sets of images. Not all image sets are created equal! Many only capture a small section of the brain, or don't have enough images for a good recreation, or the images don't show the brain's structure clearly enough, or it's too low of a resolution, or...

Yeah, there's a lot that can go wrong. So when selecting an image set, here are some good criteria to meet, in order of importance:

  • The entire brain must be captured, from the subcortical base to the tip of the skull
  • The slices must very clearly show the folds and internal structures of the brain
  • The brain must clearly have a gap between it and the skull in most of the slices
  • With more slices, more detail and accuracy can be achieved in the final output
  • Higher resolution images are better
    • Try for at minimum 350x350
    • Lower resolutions can fail outright

Below is the scan I used to make this 3D model. It is 400x512, with 160 slices. This is the scan that I found in my study that worked the best (it's test_scan.zip):

A Perfect Scan

The images will most likely either be in what's called DICOM formatting, or NIfTI formatting. DICOM image sets are usually a folder filled with a bunch of numbered files, usually with no extension. NIfTI image sets are a single file with a .nii file extension.

Neither of these image formats are supported by your computer by default, but the CD they gave you with your MRI data on it usually has a viewer program that works for Windows. Alternatively, you could use this very handy website which supports every file format, even the non-mesh 3D surfaces behind the scenes of FreeSurfer!

Find the best image set of your study, using the above rubric. If your image set is in DICOM format, you must pack them into a .zip file, in the main directory (NOT a sub-folder!). Here is the file structure expected:

  • my_scan.zip
    • IMG000001
    • IMG000002
    • IMG000003
    • ...

When you have either your DICOM .zip file, or your NIfTI .nii file ready to go, go back to the browser. In the upper left, click the Upload button which looks like an up arrow with a line behind it. Select your file and it will be uploaded to the server for processing.

Now, click Terminal in the Other category. Here, you can use the following commands to create an .stl of the surface of the brain from medical imaging data:

  • dicom2stl
    • Takes a .zip file with the DICOM images from a head study in the main directory.
  • nii2stl
    • Takes a .nii file with the NIfTI images from a head study.

All of these commands, if they complete successfully, will copy the final .stl to the main directory, brain_[NAME]_[CORTICAL]_[SMOOTH].stl, where:

  • [NAME] is the name of the input file.
  • [CORTICAL] is ether
    • cortical if only the cortical structure was captured.
    • cort+subcort if both the cortical and subcortical structures were captured.
  • [SMOOTH] is whether the output could have laplacian smoothing applied.
    • smooth if smoothed
    • raw if smoothing failed

An example command, to convert the included DICOM test scan into a .stl, would be dicom2stl test_scan.zip.

Converting your brain will take quite a few hours to complete (anywhere from 8 hours to a couple days, depending). I recommend you configure your Docker daemon to use most if not all of your CPU's cores.

To download files (like your shiny new .stl), right click the file in the browser to the left and select Download.

Once you have all the files you want to save downloaded, you can kill the server by clicking Quit in the upper right corner. When you do this, all files uploaded or created that were not downloaded will be forever lost, so be careful!

If you close your browser without clicking Quit, the image will still be running in the background. You can reconnect by going to 127.0.0.1:8888.

The other way to kill the server is to shutdown the Docker container manually. You would use docker ps to get the ID of it, then docker rm -f [ID]. This will also permenently delete all files uploaded/created.

The conversion process concatenates the two cortical hemispheres and subcortical models, then trys to smooth them together. This means that you can seperate your brain into it's constituent parts by using a 3D editing program (like Blender) to seperate the disconnected meshes ("loose parts" in Blender). If you try and print it as a whole, your printer should print just one solid object, no issues.

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A Docker image for painlessly converting head MRI data to a 3D surface model of the brain.

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