I’m totally new to Slicer and fairly new to DICOM, working on CT data. My use-case is using Slicer to export data-sets for real-time rendering and high performance.
I’ve already seen tutorials on using Slicer to create 3D meshes/surfaces from my CT dataset using thresholds, and I think these meshes can be saved as STL(?)
Another thing I’d like to do is convert the DICOM CT dataset into a raw 3D volume and export this as a 3D texture/image. I’m not sure I know the correct terminology because while I find material on volume rendering, this specific task I cannot find instructions for. Is it something I can easily do?
You can visualize many structures very nicely using volume rendering of the CT volume. To get nice colorful images, you need to map CT voxel values to color&opacity RGBA values (and there are a couple of tricks to make the rendering faster and nicer). Volume rendering is a well-established technique, most likely you can find existing implementation on any platforms, so probably you don’t need to implement it yourself.
I can appreciate many toolkits automatically do volumetric rendering from
a set of slices, but I would still be interested to know if there is a way
I can directly export this. In other words use Slicer to load a CT
dataset’s set of slices, and export effectively just a 3D array of this.
For real-time, performance rendering, 3D textures may be applied to
polygonal meshes so having the volumetric data in this raw form is still
useful to me.
Since as I understand it a CT scan contains multiple sets of slices from
multiple axes, how to combine these is not obvious to me… I could simply
take all the slices in one axes and stack them into a volume but that would
lose a substantial amount of data!
Apologies if this isn’t clear, the terminology I use is not necessarily the
same as yours.
Volume rendering is only a visualization technique. There is no way to “export” volume rendering, because it is created directly from the CT volume and a transfer function determining the colors and opacities for the density values in the CT voxels. Read more here