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REF: Refactor motion-related data computation functions #188

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REF: Refactor motion-related data computation functions #188

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8 changes: 5 additions & 3 deletions docs/notebooks/bold_realignment.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -478,7 +478,7 @@
"source": [
"from nitransforms.resampling import apply\n",
"\n",
"from nifreeze.registration.utils import displacement_framewise\n",
"from nifreeze.registration.utils import compute_fd_from_transform\n",
"\n",
"afni_fd = {}\n",
"nitransforms_fd = {}\n",
Expand All @@ -501,7 +501,9 @@
" ]\n",
"\n",
" nii = nb.load(DATA_PATH / bold_run)\n",
" nitransforms_fd[str(bold_run)] = np.array([displacement_framewise(nii, xfm) for xfm in xfms])\n",
" nitransforms_fd[str(bold_run)] = np.array(\n",
" [compute_fd_from_transform(nii, xfm) for xfm in xfms]\n",
" )\n",
"\n",
" hmc_xfm = nt.linear.LinearTransformsMapping(xfms)\n",
" out_nitransforms = (\n",
Expand All @@ -520,7 +522,7 @@
" OUTPUT_DIR / bold_run.parent / f\"{bold_run.name.rsplit('_', 1)[0]}_desc-hmc_xfm.txt\"\n",
" )\n",
" afni_fd[str(bold_run)] = np.array(\n",
" [displacement_framewise(nii, afni_xfms[i]) for i in range(len(afni_xfms))]\n",
" [compute_fd_from_transform(nii, afni_xfms[i]) for i in range(len(afni_xfms))]\n",
" )\n",
"\n",
" out_afni = (\n",
Expand Down
34 changes: 3 additions & 31 deletions docs/notebooks/pet_motion_estimation.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -2437,45 +2437,17 @@
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"from nifreeze.registration.utils import compute_fd_from_motion, extract_motion_parameters\n",
"\n",
"def extract_motion_parameters(affine):\n",
" \"\"\"Extract translation (mm) and rotation (degrees) parameters from an affine matrix.\"\"\"\n",
" translation = affine[:3, 3]\n",
" rotation_rad = np.arctan2(\n",
" [affine[2, 1], affine[0, 2], affine[1, 0]], [affine[2, 2], affine[0, 0], affine[1, 1]]\n",
" )\n",
" rotation_deg = np.rad2deg(rotation_rad)\n",
" return *translation, *rotation_deg\n",
"\n",
"\n",
"def compute_fd(motion_parameters):\n",
" \"\"\"Compute Framewise Displacement from motion parameters.\"\"\"\n",
" translations = motion_parameters[:, :3]\n",
" rotations_deg = motion_parameters[:, 3:]\n",
" rotations_rad = np.deg2rad(rotations_deg)\n",
"\n",
" # Compute differences between consecutive frames\n",
" d_translations = np.vstack([np.zeros((1, 3)), np.diff(translations, axis=0)])\n",
" d_rotations = np.vstack([np.zeros((1, 3)), np.diff(rotations_rad, axis=0)])\n",
"\n",
" # Convert rotations from radians to displacement on a sphere (radius 50 mm)\n",
" radius = 50 # typical head radius in mm\n",
" rotation_displacement = d_rotations * radius\n",
"\n",
" # Compute FD as sum of absolute differences\n",
" fd = np.sum(np.abs(d_translations) + np.abs(rotation_displacement), axis=1)\n",
" return fd\n",
"\n",
"\n",
"# Assume 'affines' is the list of affine matrices you computed earlier\n",
"# Assume `affines` is the list of affine matrices computed earlier\n",
"motion_parameters = []\n",
"\n",
"for idx, affine in enumerate(affines):\n",
" tx, ty, tz, rx, ry, rz = extract_motion_parameters(affine)\n",
" motion_parameters.append([tx, ty, tz, rx, ry, rz])\n",
"\n",
"motion_parameters = np.array(motion_parameters)\n",
"estimated_fd = compute_fd(motion_parameters)\n",
"estimated_fd = compute_fd_from_motion(motion_parameters)\n",
"\n",
"# Creating a DataFrame for better visualization\n",
"df_motion = pd.DataFrame(\n",
Expand Down
69 changes: 65 additions & 4 deletions src/nifreeze/registration/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,11 +32,15 @@
from __future__ import annotations

from itertools import product
from typing import Tuple

import nibabel as nb
import nitransforms as nt
import numpy as np

RADIUS = 50.0
"""Typical radius (in mm) of a sphere mimicking the size of a typical human brain."""


def displacements_within_mask(
mask_img: nb.spatialimages.SpatialImage,
Expand Down Expand Up @@ -79,11 +83,11 @@ def displacements_within_mask(
return np.linalg.norm(diffs, axis=-1)


def displacement_framewise(
def compute_fd_from_transform(
img: nb.spatialimages.SpatialImage,
test_xfm: nt.base.BaseTransform,
radius: float = 50.0,
):
radius: float = RADIUS,
) -> float:
"""
Compute the framewise displacement (FD) for a given transformation.

Expand All @@ -95,7 +99,6 @@ def displacement_framewise(
The transformation to test. Applied to coordinates around the image center.
radius : :obj:`float`, optional
The radius (in mm) of the spherical neighborhood around the center of the image.
Default is 50.0 mm.

Returns
-------
Expand All @@ -112,3 +115,61 @@ def displacement_framewise(
fd_coords = np.array(list(product(*((radius, -radius),) * 3))) + center_xyz
# Compute the average displacement from the test transformation
return np.mean(np.linalg.norm(test_xfm.map(fd_coords) - fd_coords, axis=-1))


def compute_fd_from_motion(motion_parameters: np.ndarray, radius: float = RADIUS) -> np.ndarray:
"""Compute framewise displacement (FD) from motion parameters.

Each row in the motion parameters represents one frame, and columns
represent each coordinate axis ``x``, `y``, and ``z``. Translation
parameters are followed by rotation parameters column-wise.

Parameters
----------
motion_parameters : :obj:`numpy.ndarray`
Motion parameters.
radius : :obj:`float`, optional
Radius (in mm) of a sphere mimicking the size of a typical human brain.

Returns
-------
:obj:`numpy.ndarray`
The framewise displacement (FD) as the sum of absolute differences
between consecutive frames.
"""

translations = motion_parameters[:, :3]
rotations_deg = motion_parameters[:, 3:]
rotations_rad = np.deg2rad(rotations_deg)

# Compute differences between consecutive frames
d_translations = np.vstack([np.zeros((1, 3)), np.diff(translations, axis=0)])
d_rotations = np.vstack([np.zeros((1, 3)), np.diff(rotations_rad, axis=0)])

# Convert rotations from radians to displacement on a sphere
rotation_displacement = d_rotations * radius

# Compute FD as sum of absolute differences
return np.sum(np.abs(d_translations) + np.abs(rotation_displacement), axis=1)


def extract_motion_parameters(affine: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
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Not sure if this module is the most appropriate place for this function.

"""Extract translation (mm) and rotation (degrees) parameters from an affine matrix.

Parameters
----------
affine : :obj:`~numpy.ndarray`
The affine transformation matrix.

Returns
-------
:obj:`tuple`
Extracted translation and rotation parameters.
"""

translation = affine[:3, 3]
rotation_rad = np.arctan2(
[affine[2, 1], affine[0, 2], affine[1, 0]], [affine[2, 2], affine[0, 0], affine[1, 1]]
)
rotation_deg = np.rad2deg(rotation_rad)
return *translation, *rotation_deg