mri_synthmorph

NAME
        mri_synthmorph - register 3D brain images without preprocessing

SYNOPSIS
        mri_synthmorph [-h] command [options]

DESCRIPTION
        SynthMorph is a deep-learning tool for symmetric, acquisition-agnostic
        registration of single-frame brain MRI of any geometry. The registration
        is anatomy-aware, removing the need for skull-stripping, and you can
        control the warp smoothness.

        Pass an option or command from the following list. You can omit trailing
        characters, as long as there is no ambiguity.

        register
                Register 3D brain images without preprocessing.

        apply
                Apply an existing transform to another 3D image or label map.

        -h
                Print this help text and exit.

IMAGE FORMAT
        The registration supports single-frame image volumes of any size,
        resolution, and orientation. The moving and the fixed image geometries
        can differ. The accepted image file formats are: MGH (.mgz) and NIfTI
        (.nii.gz, .nii).

        Internally, the registration converts image buffers to: isotropic 1-mm
        voxels, intensities min-max normalized into the interval [0, 1], and
        left-inferior-anterior (LIA) axes. This conversion requires intact
        image-to-world matrices. That is, the head must have the correct
        anatomical orientation in a viewer like freeview.

TRANSFORM FORMAT
        SynthMorph transformations operate in physical RAS space. We save matrix
        transforms as text in LTA format (.lta) and displacement fields as
        images with three frames indicating shifts in RAS direction.

ENVIRONMENT
        The following environment variables affect mri_synthmorph:

        SUBJECTS_DIR
                Ignored unless mri_synthmorph runs inside a container. Mounts
                the host directory SUBJECTS_DIR to /mnt inside the container.
                Defaults to the current working directory.

SEE ALSO
        For converting, composing, and applying transforms, consider FreeSurfer
        tools lta_convert, mri_warp_convert, mri_concatenate_lta,
        mri_concatenate_gcam, and mri_convert.

CONTACT
        Reach out to freesurfer@nmr.mgh.harvard.edu or at
        https://voxelmorph.net.

REFERENCES
        If you use SynthMorph in a publication, please cite us!

        SynthMorph: learning contrast-invariant registration without acquired
        images
        Hoffmann M, Billot B, Greve DN, Iglesias JE, Fischl B, Dalca AV
        IEEE Transactions on Medical Imaging, 41 (3), 543-558, 2022
        https://doi.org/10.1109/TMI.2021.3116879

        Anatomy-specific acquisition-agnostic affine registration learned from
        fictitious images
        Hoffmann M, Hoopes A, Fischl B*, Dalca AV* (*equal contribution)
        SPIE Medical Imaging: Image Processing, 12464, 1246402, 2023
        https://doi.org/10.1117/12.2653251
        https://synthmorph.io/#papers (PDF)

        Anatomy-aware and acquisition-agnostic joint registration with
        SynthMorph
        Hoffmann M, Hoopes A, Greve DN, Fischl B*, Dalca AV* (*equal
        contribution)
        Imaging Neuroscience, 2, 1-33, 2024
        https://doi.org/10.1162/imag_a_00197

        Website: https://synthmorph.io