`niftyregw`

Pythonic wrapper for NiftyReg, providing a modern CLI and Python API for medical image registration.

NiftyReg is a suite of tools for efficient medical image registration, developed at King's College London.

Installation

pip install niftyregw

Or with uv:

uv pip install niftyregw

CLI

niftyregw --help

Affine registration

niftyregw aladin \
  --reference ref.nii.gz \
  --floating flo.nii.gz \
  --output-affine affine.txt \
  --output-result result.nii.gz

Non-rigid registration

niftyregw f3d \
  --reference ref.nii.gz \
  --floating flo.nii.gz \
  --input-affine affine.txt \
  --output-cpp cpp.nii.gz \
  --output-result result.nii.gz

All subcommands

Subcommand	Description
`install`	Download and install NiftyReg binaries
`aladin`	Block-matching global (affine/rigid) registration
`f3d`	Fast Free-Form Deformation non-rigid registration
`measure`	Compute similarity measures between images
`jacobian`	Compute Jacobian-based maps from transformations
`resample`	Resample an image with a given transformation
`tools`	Image manipulation tools
`average`	Average images or transformations
`transform`	Manipulate and compose transformations

Python

from niftyregw import reg_aladin

reg_aladin(
    reference="ref.nii.gz",
    floating="flo.nii.gz",
    output_affine="affine.txt",
    output_result="result.nii.gz",
    rigid_only=True,
)

For any binary, use the generic run function:

from niftyregw import run

run("reg_f3d", "-ref", "ref.nii.gz", "-flo", "flo.nii.gz")

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