Nifti to DICOM-RT structure conversion

Operating system: Windows 10
Slicer version: Slicer 4.11.20200930

Hi all,

I have a binary mask in a Nifti file and I want to convert it into a DicomRT structure. I have tried 3D Slicer to perform this conversion using Dicom export plugins. Also, I have found a package, RT-Utils, that deals with it. However, the resulted DicomRT structures of both tools are not exactly the same.

Can anyone give me some details about this exportation in 3D Slicer?

I think the problem may be due to the way of extracting/storing the contours (e.g., the interpolation method), which may be somewhat different for both tools, thus providing slightly different results.

Can anyone ensure me that the exportation in 3D Slicer is robust? Has it being tested with “round-trip” experiments from Nifti to DicomRT and back (from DicomRT to Nifti).

Thanks in advance.

DICOM RTSTRUCT cannot store arbitrarily shaped segments. It was developed decades ago for storing manually drawn contours. I would strongly recommend to use to DICOM Segmentation Object to store segmentations, which allows lossless storage of binary labelmaps.

Slicer uses Plastimatch library for RTSTRUCT export. You can look up papers about this library to see what validations were done. Maybe @gcsharp can give you some pointers, too.

The plastimatch algorithm uses marching squares within image planes to generate planar polygons from a binary image. No special interpolation is done, meaning that polygon vertices lie at voxel face centers. The output will vary according to the resolution of the referenced image (the CT); if the referenced image has a different resolution than the Nifti file, this could affect round trip calculations.

In the past I have performed round trip tests within plastimatch and the sequence image → RTSTRUCT → image produces an output identical to the input. However, I have not tried this in 3D Slicer, which uses a different implementation for DICOM import and rasterization.


Thanks a lot for your quick replies and the valuable information given.
It has already helped me.

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