3D Slicer DICOM Mask Annotation

I have a mixed set of CT and MRI DICOM studies that need to be fully segmented in 3D Slicer. The goal is to generate clean, voxel-accurate volumetric masks I can feed directly into my AI training pipeline, so consistency across cases is critical.

The dataset covers three anatomical regions—brain, chest and abdomen—and I will supply them already grouped by body part. For each series I need a single multi-label mask (or separate binary masks if that is easier for you) exported in a format 3D Slicer handles natively such as NRRD or NIfTI, together with the corresponding DICOM header preserved.

Please follow these guidelines:
• Use 3D Slicer’s Segment Editor tools (e.g., Threshold, Grow from Seeds, Scissors) rather than external software so the project stays reproducible.
• Keep label IDs identical across all volumes (e.g., 1 = brain tissue, 2 = CSF, 3 = lungs, etc.); I’ll share the exact label map at kickoff.
• Masks must be watertight—no holes, no stray voxels—and aligned perfectly with the original image grid.
• Deliver each case in its own folder: /Images (DICOM) and /Masks (NRRD or .nii.gz).

When you reply, let me know your experience segmenting both CT and MRI in 3D Slicer, any automated tools or scripts you rely on, and a rough turnaround time per study (brain, chest, abdomen). I’m ready to start as soon as we agree on workflow.