Brain registration (brainreg), segmentation post-processing, and visualization for use-case / paper workflows.

This workflow has three phases:

1. Registration (SLURM): run brainreg to create per-subject output folders with registered_atlas.tiff.
2. Segmentation + probe annotations (Napari): open the registered subject outputs, add probe tracks/injections, and save into the subject’s segmentation/ folder.
3. Visualization (Python): render probe HTML and/or atlas+region PNG views from segmentation/atlas_space/.

SLURM scripts, data, and outputs are kept together in one project folder (e.g. your NFS project directory). The SLURM config expects:

• PROJECT_DIR/data — input TIFs (any subdirs)
• PROJECT_DIR/brainreg_outputs_<atlas>/ — registration outputs

Copy/symlink the bg_viz_pipeline/slurm/ folder into your project folder (preserving the slurm/ subfolder), and edit slurm/brainreg_config.sh to set PROJECT_DIR.

See bg_viz_pipeline/slurm/README.md for details of how the SLURM scripts work and how to run them.

At a minimum:

• edit slurm/brainreg_config.sh
• run ./slurm/submit_brainreg.sh

For each registered subject folder created by Phase 1:

1. Open the subject in napari using your brainrender/segmentation workflow.
2. Add probe tracks/injections.
3. Save back into the subject's segmentation/ folder in the locations expected by the Python visualizers:
   • segmentation/atlas_space/tracks/*.npy
   • optional segmentation/atlas_space/regions/*.obj

From the workflows repo root (so the bg_viz_pipeline/ package is importable):

1. Probe HTML:

   • python -m bg_viz_pipeline.scripts.probes_to_html <atlas> <brainreg_dir> <out.html> [--regions ...]

2. Atlas viewer PNGs:

   • configure bg_viz_pipeline/presets/viewer_presets.json, then run:

python -m bg_viz_pipeline.scripts.brainreg_viewer              # all presets
python -m bg_viz_pipeline.scripts.brainreg_viewer --only-subject ROI-1
python -m bg_viz_pipeline.scripts.brainreg_viewer --only-subdir ds_MPX-R-0033_...

Use a conda environment with BrainGlobe installed (e.g. brainglobe-env; pip install brainglobe).