coregistered

Coregistered refers to data or images that have been aligned to a shared coordinate system via a coregistration process. In medical and neuroimaging, coregistered data enable direct voxel-wise comparison and integration across different modalities (for example, magnetic resonance imaging MRI and positron emission tomography PET) or across different time points. The term describes the outcome after the alignment step, not the original raw data.

Coregistration involves selecting a reference (target) image and estimating a spatial transformation that maps each source image into the target’s space. Transformations range from rigid (rotation and translation) to affine (including scaling and shearing) and nonrigid/deformable models that account for local differences. The alignment is driven by an objective function such as mutual information for multi-modality data or cross-correlation for similar modalities, typically optimized iteratively. After estimation, the source images are resampled onto the target grid, with considerations for interpolation quality and potential data degradation.

Applications include multimodal fusion, atlas-based analyses, and longitudinal studies. Challenges include geometric distortions, patient motion, differences in resolution and field of view, and partial volume effects. Popular software tools include FSL, ANTs, SPM, and elastix, each offering a range of rigid, affine, and nonrigid registration algorithms. The quality of coregistration is often assessed with visual inspection and quantitative metrics such as similarity scores or landmark error.