Example: Registration Validation

Validation is a separate stage from optimization. A registration can improve a metric while violating geometry, producing an empty resample, or moving a label boundary in the wrong direction. A useful report combines:

• shape and physical-frame checks;
• metric values before and after;
• overlap measures when labels exist; and
• convergence state and iteration budget.

The CT/MR registration example demonstrates the visual part of this contract: it renders identity and registered overlays with red/green fringes and a data-derived MR resampling-change map.

For a label-space check, use the statistics facade after resampling both label maps onto one grid:

let dice = ritk_statistics::dice_coefficient(&fixed_labels, &moving_labels)?;
let hausdorff = ritk_statistics::hausdorff_distance(&fixed_labels, &moving_labels)?;

The exact statistics signature depends on the label representation, so the validation layer must keep the conversion at the boundary and report the input shapes with the metric values. Never accept only an is_ok result: record the value, units, reference frame, and threshold used for the decision.

Source and verification

The visual source is crates/ritk-registration/examples/book_registration.rs.

cargo run -p ritk-registration --example book_registration -- \
  docs/book/figures/ct_mri_registration.svg

The registration example requires normalized mutual information to improve from identity to the dataset transform, preserves the full CT grid, and reports maximum and mean absolute MR resampling change. The registration and statistics test suites provide the numerical oracles; the figures are checked for correct labels, shared display conventions, and visible pre/post change.