Getting started with 3D Slicer

3D Slicer is an imaging suite that supports almost all functionalities a biologist would need to process volumetric datasets (CT/CBCT, MR, OCT, OPT, EM,…). Some of its key features are: Reading image stacks (DICOM and else), format conversion, segmentation, image processing (filters), 3D visualization, making surface models and measurements (distances, angle, surface areas, volumes and recording landmarks coordinates). It works on all major OSes (Windows, Mac and Linux). More features outside of the core functionality is available through the Extension Manager. Computationally apt people can design their own functionalities and extend its feature set by using the built-in Python Interactor.

A few words of caution: Slicer is a research software that’s under constant and active (and I do mean active, as in daily feature additions) development. As such, some of state-of-the-art functionalities can be experimental, and may not be refined. Having said that, I have been using Slicer for more than 5 years and the core modules I use (Volume rendering, volumes, transforms, segmentation) is as solid as any commercial package. When it fails, it is usually due to lack of sufficient RAM.

How to get started with 3D Slicer?

Once you download the software go to the New Users Wiki, and familiarize yourself with the UI. These two tutorials are a must.

  1. https://www.slicer.org/wiki/Documentation/4.6/Training#Slicer_Welcome_Tutorial
  2. https://www.slicer.org/w/images/5/51/3DDataLoadingandVisualization_Slicer4.5_SoniaPujol.pdf

Depending on the task, there are useful videos and tutorials on the youtube. Make sure to check out the FAQ.

There is an excellent introduction to Slicer by the Open Source Paleontologist. Unfortunately, given the pace of development in Slicer, it is now quite a bit dated. While the workflow and processing steps are still valid, menus and modules are quite different than the version used for that tutorial and there are now more tools which wasn’t available at the time.

Slicer contains some example datasets (brain MR, facial CBCT, chest CT etc) for your to play with right away.

In addition to these, I will be adding step-by-step tutorial for common tasks using publicly available datasets from imaging repositories such as DigiMorph and MorphoSource.

I need more help? Once you completed the tutorials and did a reasonable effort to search for FAQ and documentation on Slicer website and yet still have some unanswered questions, you might get help from the community. You can browse archives of the user list at http://slicer-users.65878.n3.nabble.com/. If you still couldn’t find an answer, feel free to post a question at the Slicer forum (https://discourse.slicer.org/)

Your likelihood of getting answers will be much higher, if you ask a well-framed question with sufficient (not too much) specifics of what you want to accomplish and the issues you encountered (“How can I read my CT scans into Slicer” would be a poor question).

If you end up publishing research that you conduct with the help of Slicer, please cite it, and add your publication to the DB. As an open-source publicly funded project, this is the only way to secure its future support and development.

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