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registration-alignment

registration-alignment

Reslice Dipy images, configure affine and SyN registration, apply transforms, correct DWI motion, and align streamlines or bundles.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: registration-alignment description: "Reslice Dipy images, configure affine and SyN registration, apply transforms, correct DWI motion, and align streamlines or bundles." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Dipy Registration And Alignment

Use this sub-skill when a task involves Dipy spatial resampling, affine image registration, SyN/diffeomorphic registration, applying saved transforms, between-volume DWI motion correction, streamline linear registration, or BundleWarp bundle deformation. Keep this file as the router; detailed API choices, CLI recipes, and failure recovery live in the bundled references.

Route Here For

  • Reslicing or resampling 3D/4D image arrays to new voxel sizes with dipy.align.reslice.reslice or dipy_reslice.
  • Choosing and configuring center-of-mass, translation, rigid, scaling, or affine image registration.
  • Running SyN registration with CC, SSD, or EM metrics and saving/applying displacement fields.
  • Applying affine .txt or diffeomorphic displacement-field transforms to images.
  • Correcting between-volume DWI motion from a 4D image plus b-values/b-vectors.
  • Running streamline linear registration (SLR) or BundleWarp when bundle geometry, not voxel data, is the registration target.

Route Elsewhere

  • NIfTI loading/saving, b-values/b-vectors, headers, tractogram reference handling, and format conversion: ../io-data/.
  • Tractography, streamline clustering, bundle recognition, segmentation outputs, and tractometry after alignment: ../tracking-segmentation/.
  • Generic Dipy CLI discovery, parser behavior, and cross-family command inventories: ../cli-workflows/.
  • Model fitting, peaks, ODFs, tensor maps, or DWI reconstruction before/after alignment: ../reconstruction-models/.

Bundled Runtime References

  • references/api-reference.md summarizes the registration APIs, transform objects, metrics, and owned CLI entry points.
  • references/workflows.md gives safe recipes for reslice, affine/SyN registration, transform application, motion correction, SLR, and BundleWarp.
  • references/troubleshooting.md maps symptoms to causes, concrete recovery actions, and validation checks.
  • scripts/dipy_reslice_smoke.py runs a deterministic tiny 3D reslice check and prints JSON.

Safe Defaults

  • Start with a small crop or synthetic array before full-resolution whole-volume registration.
  • Preserve and validate affines: moving data is transformed into static/reference space, and saved aligned images should use the static affine.
  • Prefer affine or rigid registration for global pose/scale mismatch; add SyN only when nonlinear anatomical deformation is scientifically justified.
  • Avoid assuming matplotlib, FURY, or display backends are installed; visual overlays from dipy.viz.regtools are optional QA, not required for runtime validation.
  • For labels or masks, use nearest-neighbor interpolation; for scalar anatomical images, linear interpolation is usually safer.

Minimal Validation

Run the bundled smoke script before deeper debugging:

python scripts/dipy_reslice_smoke.py

Expected output is JSON with ok: true, a changed shape, a changed affine diagonal consistent with the target voxel size, and preserved value range for the tiny synthetic volume.

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