Add multi-MRI preprocessing with rigid registration and averaging

[Copilot]

Previously raised error on multiple MRI images per subject. Now handles them via rigid registration and averaging with optional super-resolution.

Workflow

Multi-MRI path:

1. n4_mri_individual - N4 correction per image → desc-N4_mriidx-{N}
2. register_mri_to_first - Greedy 6-DOF rigid to first image → transforms
3. average_mri - Apply transforms with optional upsampling, average → desc-preproc
4. n4_mri - Copy to desc-N4 for downstream compatibility

Single-MRI path unchanged: direct N4 application.

Key Changes

New rules:

• n4_mri_individual - Per-image N4 (multi-MRI only)
• register_mri_to_first - Rigid registration using greedy
• average_mri - Transform + average with upsampling support

New scripts:

• average_registered_mri.py - Applies transformations with optional upsampling, averages images
• copy_or_n4.py - Routes single vs multi-MRI cases for final output

Configuration:

• --mri_upsample_factor - Super-resolution factor (default: 1.0)

Example

spimquant /path/to/bids /output participant \
  --register_to_mri \
  --mri_upsample_factor 2.0

Processes 3 MRI acquisitions → N4 each → rigid align → 2× upsample during transform → average for super-resolved output.

Warning

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• pixi.sh
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Original prompt

add a new set of rules to the preproc_mri sml file to deal with multiple matched MRI images (right now an error is raised), including a rule to rigidly register each MRI image to the first one, and then a rule to average all of those images. use greedy for the rigid reg. add an option to upsample the images before averaging (upsample and apply xfm in same step) for effectively superresolvrd images. perform n4 before averaging. call the reconstructed image desc-preproc.

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