3D medical image visualization tools
Hi everyone. You are going to expand your knowledge on 3D medical image visualization in Python by going through this article.
The code implementation for 3D image visualization is discussed below. There are many python libraries (Matplotlib, OpenCV) available for 2D image visualization. When we try to visualize a 3D image using Matplotlib, we get the following error message.
Viewing 3D images in a flat 2D browser is difficult. However, using above mentioned libraries, we can visualize a 3D image slice by slice.
In slices, it is hard to see some properties of the 3D image (3D object orientation, visualize all side views). Therefore, we need 3D visualization tools and libraries. There are some free-source software tools available for 3D image visualization.
1. Fiji — http://fiji.sc/Fiji
2. ImageJ — http://imagej.nih.gov/ij/
3. 3D slicer — http://www.slicer.org/
4. Drishti — https://github.com/nci/drishti
5. ITKsnap — http://www.itksnap.org
6. TurtleSeg — http://www.turtleseg.org/
7. MRIcro — http://www.cabiatl.com/mricro/mricro/mricro.html
8. Paraview — http://www.paraview.org/
Throughout this article, I am going to discuss 3D image visualization Python packages and examples.
1. Itkwidgets — 3D visualization in the browser — https://github.com/InsightSoftwareConsortium/itkwidgets
2. Napari — multidimensional image viewer in python — https://napari.org/
Now we will look into some code for 3D image visualization in the above-mentioned python packages. As a first step, we load the 3D image to the workspace.
- Image visualization with Itkwidgets
2. Image visualization with Napari
We can change the properties of the loaded image in the Itkwidgets and Napari GUI and can visualize the images in greater detail. The GUIs are very easy to handle.
Thank you everyone for reading! I hope this article will be useful in your projects.
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