What problem does it solve? Processing PET neuroimaging data requires coordinating multiple tools for coregistration, spatial normalization, reference region extraction, and SUVR quantification, which is error-prone when done manually across tracers like PiB, FDG, and tau. ## Core Features & Use Cases - PET-to-T1w Coregistration and MNI Normalization: Registers PET frames to structural T1w space and optionally warps to MNI152 standard space via FSL FLIRT/FNIRT. - SUVR Computation: Computes Standardized Uptake Value Ratios from target ROIs and tracer-appropriate reference regions, outputting per-region CSV values and optional voxelwise SUVR maps. - Tracer-Specific Workflows: Supports PiB amyloid (cerebellar cortex reference), FDG metabolism (pons reference), and flortaucipir tau imaging with documented SUVR thresholds. - Use Case: Given a PiB PET scan and a FreeSurfer-parcellated T1w image, coregister the PET to T1w space, extract the cerebellar cortex reference region, and compute cortical SUVR values to assess amyloid positivity against the 1.42 threshold. ## Quick Start Use the pet-skill to coregister my PiB PET scan to the T1w image and compute SUVR values using the cerebellar cortex as the reference region.
