feat: add mask statistics getter functions in Segmentation

[strixy16]

By mask I mean any non-zero voxels in the label_image.

Functions added to the Segmentation class:

• Get label (voxel value in image) from the name in roi_indices dictionary
• Get the bounding box around the mask in the label_image
• Get the size dimensions (w,h,d) of the mask in the label_image
• Get the number of pixels in the mask in the label_image - specifically didn't call this volume because it's not technically the volume in real world measurements, but useful for size comparison across patients or ROIs

Other updates:

• Expanded variable v to verbose in autopipeline- had no idea what v was, this is more human readable

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[jjjermiah]

clean, can you add a couple of tests?

[codecov]

Codecov Report

Attention: Patch coverage is 48.27586% with 15 lines in your changes missing coverage. Please review.

Project coverage is 61.72%. Comparing base (155f59a) to head (29faa47).
Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
src/imgtools/modules/segmentation.py	39.13%	14 Missing ⚠️
src/imgtools/autopipeline.py	83.33%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #231      +/-   ##
==========================================
- Coverage   61.84%   61.72%   -0.12%     
==========================================
  Files          54       54              
  Lines        3866     3888      +22     
==========================================
+ Hits         2391     2400       +9     
- Misses       1475     1488      +13     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

[strixy16]

So the from_dicom method actually IS specific to DICOMs, it's just a sitk.Image that's been loaded from a DICOM. The looping over the SegmentLabel and SegmentSequence is something that's specifically retrieved from a DICOM and doesn't exist in the niftis.