/
_freesurfer.py
715 lines (612 loc) · 24.3 KB
/
_freesurfer.py
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# -*- coding: utf-8 -*-
"""Freesurfer handling functions."""
# Authors: Alex Rockhill <aprockhill@mailbox.org>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
import os.path as op
import numpy as np
from gzip import GzipFile
from .bem import _bem_find_surface, read_bem_surfaces
from .io.constants import FIFF
from .io.meas_info import read_fiducials
from .transforms import (apply_trans, invert_transform, combine_transforms,
_ensure_trans, read_ras_mni_t, Transform)
from .surface import read_surface, _read_mri_surface
from .utils import (verbose, _validate_type, _check_fname, _check_option,
get_subjects_dir, _require_version, logger)
def _check_subject_dir(subject, subjects_dir):
"""Check that the Freesurfer subject directory is as expected."""
subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
for img_name in ('T1', 'brain', 'aseg'):
if not op.isfile(op.join(subjects_dir, subject, 'mri',
f'{img_name}.mgz')):
raise ValueError('Freesurfer recon-all subject folder '
'is incorrect or improperly formatted, '
f'got {op.join(subjects_dir, subject)}')
return op.join(subjects_dir, subject)
def _get_aseg(aseg, subject, subjects_dir):
"""Check that the anatomical segmentation file exists and load it."""
_require_version('nibabel', 'load aseg', '2.1.0')
import nibabel as nib
subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
if not aseg.endswith('aseg'):
raise RuntimeError(
f'`aseg` file path must end with "aseg", got {aseg}')
aseg = _check_fname(op.join(subjects_dir, subject, 'mri', aseg + '.mgz'),
overwrite='read', must_exist=True)
aseg = nib.load(aseg)
aseg_data = np.array(aseg.dataobj)
return aseg, aseg_data
def _import_nibabel(why='use MRI files'):
try:
import nibabel as nib
except ImportError as exp:
msg = 'nibabel is required to %s, got:\n%s' % (why, exp)
else:
msg = ''
if msg:
raise ImportError(msg)
return nib
def _reorient_image(img, axcodes='RAS'):
"""Reorient an image to a given orientation.
Parameters
----------
img : instance of SpatialImage
The MRI image.
axcodes : tuple | str
The axis codes specifying the orientation, e.g. "RAS".
See :func:`nibabel.orientations.aff2axcodes`.
Returns
-------
img_data : ndarray
The reoriented image data.
vox_ras_t : ndarray
The new transform from the new voxels to surface RAS.
Notes
-----
.. versionadded:: 0.24
"""
import nibabel as nib
orig_data = np.array(img.dataobj).astype(np.float32)
# reorient data to RAS
ornt = nib.orientations.axcodes2ornt(
nib.orientations.aff2axcodes(img.affine)).astype(int)
ras_ornt = nib.orientations.axcodes2ornt(axcodes)
ornt_trans = nib.orientations.ornt_transform(ornt, ras_ornt)
img_data = nib.orientations.apply_orientation(orig_data, ornt_trans)
orig_mgh = nib.MGHImage(orig_data, img.affine)
aff_trans = nib.orientations.inv_ornt_aff(ornt_trans, img.shape)
vox_ras_t = np.dot(orig_mgh.header.get_vox2ras_tkr(), aff_trans)
return img_data, vox_ras_t
def _mri_orientation(orientation):
"""Get MRI orientation information from an image.
Parameters
----------
orientation : str
Orientation that you want. Can be "axial", "saggital", or "coronal".
Returns
-------
axis : int
The dimension of the axis to take slices over when plotting.
x : int
The dimension of the x axis.
y : int
The dimension of the y axis.
Notes
-----
.. versionadded:: 0.21
.. versionchanged:: 0.24
"""
_check_option('orientation', orientation, ('coronal', 'axial', 'sagittal'))
axis = dict(coronal=1, axial=2, sagittal=0)[orientation]
x, y = sorted(set([0, 1, 2]).difference(set([axis])))
return axis, x, y
def _get_mri_info_data(mri, data):
# Read the segmentation data using nibabel
if data:
_import_nibabel('load MRI atlas data')
out = dict()
_, out['vox_mri_t'], out['mri_ras_t'], dims, _, mgz = _read_mri_info(
mri, return_img=True)
out.update(
mri_width=dims[0], mri_height=dims[1],
mri_depth=dims[1], mri_volume_name=mri)
if data:
assert mgz is not None
out['mri_vox_t'] = invert_transform(out['vox_mri_t'])
out['data'] = np.asarray(mgz.dataobj)
return out
def _get_mgz_header(fname):
"""Adapted from nibabel to quickly extract header info."""
fname = _check_fname(fname, overwrite='read', must_exist=True,
name='MRI image')
if not fname.endswith('.mgz'):
raise IOError('Filename must end with .mgz')
header_dtd = [('version', '>i4'), ('dims', '>i4', (4,)),
('type', '>i4'), ('dof', '>i4'), ('goodRASFlag', '>i2'),
('delta', '>f4', (3,)), ('Mdc', '>f4', (3, 3)),
('Pxyz_c', '>f4', (3,))]
header_dtype = np.dtype(header_dtd)
with GzipFile(fname, 'rb') as fid:
hdr_str = fid.read(header_dtype.itemsize)
header = np.ndarray(shape=(), dtype=header_dtype,
buffer=hdr_str)
# dims
dims = header['dims'].astype(int)
dims = dims[:3] if len(dims) == 4 else dims
# vox2ras_tkr
delta = header['delta']
ds = np.array(delta, float)
ns = np.array(dims * ds) / 2.0
v2rtkr = np.array([[-ds[0], 0, 0, ns[0]],
[0, 0, ds[2], -ns[2]],
[0, -ds[1], 0, ns[1]],
[0, 0, 0, 1]], dtype=np.float32)
# ras2vox
d = np.diag(delta)
pcrs_c = dims / 2.0
Mdc = header['Mdc'].T
pxyz_0 = header['Pxyz_c'] - np.dot(Mdc, np.dot(d, pcrs_c))
M = np.eye(4, 4)
M[0:3, 0:3] = np.dot(Mdc, d)
M[0:3, 3] = pxyz_0.T
header = dict(dims=dims, vox2ras_tkr=v2rtkr, vox2ras=M,
zooms=header['delta'])
return header
def _get_atlas_values(vol_info, rr):
# Transform MRI coordinates (where our surfaces live) to voxels
rr_vox = apply_trans(vol_info['mri_vox_t'], rr)
good = ((rr_vox >= -.5) &
(rr_vox < np.array(vol_info['data'].shape, int) - 0.5)).all(-1)
idx = np.round(rr_vox[good].T).astype(np.int64)
values = np.full(rr.shape[0], np.nan)
values[good] = vol_info['data'][tuple(idx)]
return values
def get_volume_labels_from_aseg(mgz_fname, return_colors=False,
atlas_ids=None):
"""Return a list of names and colors of segmented volumes.
Parameters
----------
mgz_fname : str
Filename to read. Typically aseg.mgz or some variant in the freesurfer
pipeline.
return_colors : bool
If True returns also the labels colors.
atlas_ids : dict | None
A lookup table providing a mapping from region names (str) to ID values
(int). Can be None to use the standard Freesurfer LUT.
.. versionadded:: 0.21.0
Returns
-------
label_names : list of str
The names of segmented volumes included in this mgz file.
label_colors : list of str
The RGB colors of the labels included in this mgz file.
See Also
--------
read_freesurfer_lut
Notes
-----
.. versionchanged:: 0.21.0
The label names are now sorted in the same order as their corresponding
values in the MRI file.
.. versionadded:: 0.9.0
"""
import nibabel as nib
if not op.isfile(mgz_fname):
raise IOError('aseg file "%s" not found' % mgz_fname)
atlas = nib.load(mgz_fname)
data = np.asarray(atlas.dataobj) # don't need float here
want = np.unique(data)
if atlas_ids is None:
atlas_ids, colors = read_freesurfer_lut()
elif return_colors:
raise ValueError('return_colors must be False if atlas_ids are '
'provided')
# restrict to the ones in the MRI, sorted by label name
keep = np.in1d(list(atlas_ids.values()), want)
keys = sorted((key for ki, key in enumerate(atlas_ids.keys()) if keep[ki]),
key=lambda x: atlas_ids[x])
if return_colors:
colors = [colors[k] for k in keys]
out = keys, colors
else:
out = keys
return out
##############################################################################
# Head to MRI volume conversion
@verbose
def head_to_mri(pos, subject, mri_head_t, subjects_dir=None,
verbose=None):
"""Convert pos from head coordinate system to MRI ones.
This function converts to MRI RAS coordinates and not to surface
RAS.
Parameters
----------
pos : array, shape (n_pos, 3)
The coordinates (in m) in head coordinate system.
%(subject)s
mri_head_t : instance of Transform
MRI<->Head coordinate transformation.
%(subjects_dir)s
%(verbose)s
Returns
-------
coordinates : array, shape (n_pos, 3)
The MRI RAS coordinates (in mm) of pos.
Notes
-----
This function requires nibabel.
"""
subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
t1_fname = op.join(subjects_dir, subject, 'mri', 'T1.mgz')
head_mri_t = _ensure_trans(mri_head_t, 'head', 'mri')
_, _, mri_ras_t, _, _ = _read_mri_info(t1_fname)
head_ras_t = combine_transforms(head_mri_t, mri_ras_t, 'head', 'ras')
return 1e3 * apply_trans(head_ras_t, pos) # mm
##############################################################################
# Surface to MNI conversion
@verbose
def vertex_to_mni(vertices, hemis, subject, subjects_dir=None, verbose=None):
"""Convert the array of vertices for a hemisphere to MNI coordinates.
Parameters
----------
vertices : int, or list of int
Vertex number(s) to convert.
hemis : int, or list of int
Hemisphere(s) the vertices belong to.
%(subject)s
subjects_dir : str, or None
Path to SUBJECTS_DIR if it is not set in the environment.
%(verbose)s
Returns
-------
coordinates : array, shape (n_vertices, 3)
The MNI coordinates (in mm) of the vertices.
"""
singleton = False
if not isinstance(vertices, list) and not isinstance(vertices, np.ndarray):
singleton = True
vertices = [vertices]
if not isinstance(hemis, list) and not isinstance(hemis, np.ndarray):
hemis = [hemis] * len(vertices)
if not len(hemis) == len(vertices):
raise ValueError('hemi and vertices must match in length')
subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
surfs = [op.join(subjects_dir, subject, 'surf', '%s.white' % h)
for h in ['lh', 'rh']]
# read surface locations in MRI space
rr = [read_surface(s)[0] for s in surfs]
# take point locations in MRI space and convert to MNI coordinates
xfm = read_talxfm(subject, subjects_dir)
xfm['trans'][:3, 3] *= 1000. # m->mm
data = np.array([rr[h][v, :] for h, v in zip(hemis, vertices)])
if singleton:
data = data[0]
return apply_trans(xfm['trans'], data)
##############################################################################
# Volume to MNI conversion
@verbose
def head_to_mni(pos, subject, mri_head_t, subjects_dir=None,
verbose=None):
"""Convert pos from head coordinate system to MNI ones.
Parameters
----------
pos : array, shape (n_pos, 3)
The coordinates (in m) in head coordinate system.
%(subject)s
mri_head_t : instance of Transform
MRI<->Head coordinate transformation.
%(subjects_dir)s
%(verbose)s
Returns
-------
coordinates : array, shape (n_pos, 3)
The MNI coordinates (in mm) of pos.
Notes
-----
This function requires either nibabel.
"""
subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
# before we go from head to MRI (surface RAS)
head_mni_t = combine_transforms(
_ensure_trans(mri_head_t, 'head', 'mri'),
read_talxfm(subject, subjects_dir), 'head', 'mni_tal')
return apply_trans(head_mni_t, pos) * 1000.
@verbose
def get_mni_fiducials(subject, subjects_dir=None, verbose=None):
"""Estimate fiducials for a subject.
Parameters
----------
%(subject)s
%(subjects_dir)s
%(verbose)s
Returns
-------
fids_mri : list
List of estimated fiducials (each point in a dict), in the order
LPA, nasion, RPA.
Notes
-----
This takes the ``fsaverage-fiducials.fif`` file included with MNE—which
contain the LPA, nasion, and RPA for the ``fsaverage`` subject—and
transforms them to the given FreeSurfer subject's MRI space.
The MRI of ``fsaverage`` is already in MNI Talairach space, so applying
the inverse of the given subject's MNI Talairach affine transformation
(``$SUBJECTS_DIR/$SUBJECT/mri/transforms/talairach.xfm``) is used
to estimate the subject's fiducial locations.
For more details about the coordinate systems and transformations involved,
see https://surfer.nmr.mgh.harvard.edu/fswiki/CoordinateSystems and
:ref:`tut-source-alignment`.
"""
# Eventually we might want to allow using the MNI Talairach with-skull
# transformation rather than the standard brain-based MNI Talaranch
# transformation, and/or project the points onto the head surface
# (if available).
fname_fids_fs = op.join(op.dirname(__file__), 'data',
'fsaverage', 'fsaverage-fiducials.fif')
# Read fsaverage fiducials file and subject Talairach.
fids, coord_frame = read_fiducials(fname_fids_fs)
assert coord_frame == FIFF.FIFFV_COORD_MRI
if subject == 'fsaverage':
return fids # special short-circuit for fsaverage
mni_mri_t = invert_transform(read_talxfm(subject, subjects_dir))
for f in fids:
f['r'] = apply_trans(mni_mri_t, f['r'])
return fids
@verbose
def estimate_head_mri_t(subject, subjects_dir=None, verbose=None):
"""Estimate the head->mri transform from fsaverage fiducials.
A subject's fiducials can be estimated given a Freesurfer ``recon-all``
by transforming ``fsaverage`` fiducials using the inverse Talairach
transform, see :func:`mne.coreg.get_mni_fiducials`.
Parameters
----------
%(subject)s
%(subjects_dir)s
%(verbose)s
Returns
-------
%(trans_not_none)s
"""
from .channels.montage import make_dig_montage, compute_native_head_t
subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
lpa, nasion, rpa = get_mni_fiducials(subject, subjects_dir)
montage = make_dig_montage(lpa=lpa['r'], nasion=nasion['r'], rpa=rpa['r'],
coord_frame='mri')
return invert_transform(compute_native_head_t(montage))
def _ensure_image_in_surface_RAS(image, subject, subjects_dir):
"""Check if the image is in Freesurfer surface RAS space."""
import nibabel as nib
if not isinstance(image, nib.spatialimages.SpatialImage):
image = nib.load(image)
image = nib.MGHImage(image.dataobj.astype(np.float32), image.affine)
fs_img = nib.load(op.join(subjects_dir, subject, 'mri', 'brain.mgz'))
if not np.allclose(image.affine, fs_img.affine, atol=1e-6):
raise RuntimeError('The `image` is not aligned to Freesurfer '
'surface RAS space. This space is required as '
'it is the space where the anatomical '
'segmentation and reconstructed surfaces are')
return image # returns MGH image for header
@verbose
def read_talxfm(subject, subjects_dir=None, verbose=None):
"""Compute MRI-to-MNI transform from FreeSurfer talairach.xfm file.
Parameters
----------
%(subject)s
%(subjects_dir)s
%(verbose)s
Returns
-------
mri_mni_t : instance of Transform
The affine transformation from MRI to MNI space for the subject.
"""
# Adapted from freesurfer m-files. Altered to deal with Norig
# and Torig correctly
subjects_dir = get_subjects_dir(subjects_dir)
# Setup the RAS to MNI transform
ras_mni_t = read_ras_mni_t(subject, subjects_dir)
ras_mni_t['trans'][:3, 3] /= 1000. # mm->m
# We want to get from Freesurfer surface RAS ('mri') to MNI ('mni_tal').
# This file only gives us RAS (non-zero origin) ('ras') to MNI ('mni_tal').
# Se we need to get the ras->mri transform from the MRI headers.
# To do this, we get Norig and Torig
# (i.e. vox_ras_t and vox_mri_t, respectively)
path = op.join(subjects_dir, subject, 'mri', 'orig.mgz')
if not op.isfile(path):
path = op.join(subjects_dir, subject, 'mri', 'T1.mgz')
if not op.isfile(path):
raise IOError('mri not found: %s' % path)
_, _, mri_ras_t, _, _ = _read_mri_info(path)
mri_mni_t = combine_transforms(mri_ras_t, ras_mni_t, 'mri', 'mni_tal')
return mri_mni_t
def _check_mri(mri, subject, subjects_dir):
"""Check whether an mri exists in the Freesurfer subject directory."""
_validate_type(mri, 'path-like', 'mri')
if op.isfile(mri) and op.basename(mri) != mri:
return mri
if not op.isfile(mri):
if subject is None:
raise FileNotFoundError(
f'MRI file {mri!r} not found and no subject provided')
subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
mri = op.join(subjects_dir, subject, 'mri', mri)
if not op.isfile(mri):
raise FileNotFoundError(f'MRI file {mri!r} not found')
if op.basename(mri) == mri:
err = (f'Ambiguous filename - found {mri!r} in current folder.\n'
'If this is correct prefix name with relative or absolute path')
raise IOError(err)
return mri
def _read_mri_info(path, units='m', return_img=False, use_nibabel=False):
# This is equivalent but 100x slower, so only use nibabel if we need to
# (later):
if use_nibabel:
import nibabel
hdr = nibabel.load(path).header
n_orig = hdr.get_vox2ras()
t_orig = hdr.get_vox2ras_tkr()
dims = hdr.get_data_shape()
zooms = hdr.get_zooms()[:3]
else:
hdr = _get_mgz_header(path)
n_orig = hdr['vox2ras']
t_orig = hdr['vox2ras_tkr']
dims = hdr['dims']
zooms = hdr['zooms']
# extract the MRI_VOXEL to RAS (non-zero origin) transform
vox_ras_t = Transform('mri_voxel', 'ras', n_orig)
# extract the MRI_VOXEL to MRI transform
vox_mri_t = Transform('mri_voxel', 'mri', t_orig)
# construct the MRI to RAS (non-zero origin) transform
mri_ras_t = combine_transforms(
invert_transform(vox_mri_t), vox_ras_t, 'mri', 'ras')
assert units in ('m', 'mm')
if units == 'm':
conv = np.array([[1e-3, 1e-3, 1e-3, 1]]).T
# scaling and translation terms
vox_ras_t['trans'] *= conv
vox_mri_t['trans'] *= conv
# just the translation term
mri_ras_t['trans'][:, 3:4] *= conv
out = (vox_ras_t, vox_mri_t, mri_ras_t, dims, zooms)
if return_img:
nibabel = _import_nibabel()
out += (nibabel.load(path),)
return out
def read_freesurfer_lut(fname=None):
"""Read a Freesurfer-formatted LUT.
Parameters
----------
fname : str | None
The filename. Can be None to read the standard Freesurfer LUT.
Returns
-------
atlas_ids : dict
Mapping from label names to IDs.
colors : dict
Mapping from label names to colors.
"""
lut = _get_lut(fname)
names, ids = lut['name'], lut['id']
colors = np.array([lut['R'], lut['G'], lut['B'], lut['A']], float).T
atlas_ids = dict(zip(names, ids))
colors = dict(zip(names, colors))
return atlas_ids, colors
def _get_lut(fname=None):
"""Get a FreeSurfer LUT."""
_validate_type(fname, ('path-like', None), 'fname')
if fname is None:
fname = op.join(op.dirname(__file__), 'data',
'FreeSurferColorLUT.txt')
_check_fname(fname, 'read', must_exist=True)
dtype = [('id', '<i8'), ('name', 'U'),
('R', '<i8'), ('G', '<i8'), ('B', '<i8'), ('A', '<i8')]
lut = {d[0]: list() for d in dtype}
with open(fname, 'r') as fid:
for line in fid:
line = line.strip()
if line.startswith('#') or not line:
continue
line = line.split()
if len(line) != len(dtype):
raise RuntimeError(f'LUT is improperly formatted: {fname}')
for d, part in zip(dtype, line):
lut[d[0]].append(part)
lut = {d[0]: np.array(lut[d[0]], dtype=d[1]) for d in dtype}
assert len(lut['name']) > 0
return lut
@verbose
def _get_head_surface(surf, subject, subjects_dir, bem=None, verbose=None):
"""Get a head surface from the Freesurfer subject directory.
Parameters
----------
surf : str
The name of the surface 'auto', 'head', 'outer_skin', 'head-dense'
or 'seghead'.
%(subject)s
%(subjects_dir)s
bem : mne.bem.ConductorModel | None
The conductor model that stores information about the head surface.
%(verbose)s
Returns
-------
head_surf : dict | None
A dictionary with keys 'rr', 'tris', 'ntri', 'use_tris', 'np'
and 'coord_frame' that store information for mesh plotting and other
useful information about the head surface.
Notes
-----
.. versionadded: 0.24
"""
_check_option(
'surf', surf, ('auto', 'head', 'outer_skin', 'head-dense', 'seghead'))
if surf in ('auto', 'head', 'outer_skin'):
if bem is not None:
try:
return _bem_find_surface(bem, 'head')
except RuntimeError:
logger.info('Could not find the surface for '
'head in the provided BEM model, '
'looking in the subject directory.')
if subject is None:
if surf == 'auto':
return
raise ValueError('To plot the head surface, the BEM/sphere'
' model must contain a head surface '
'or "subject" must be provided (got '
'None)')
subject_dir = op.join(
get_subjects_dir(subjects_dir, raise_error=True), subject)
if surf in ('head-dense', 'seghead'):
try_fnames = [op.join(subject_dir, 'bem', f'{subject}-head-dense.fif'),
op.join(subject_dir, 'surf', 'lh.seghead')]
else:
try_fnames = [op.join(subject_dir, 'bem', 'outer_skin.surf'),
op.join(subject_dir, 'bem', 'flash', 'outer_skin.surf'),
op.join(subject_dir, 'bem', f'{subject}-head.fif')]
for fname in try_fnames:
if op.exists(fname):
logger.info(f'Using {op.basename(fname)} for head surface.')
if op.splitext(fname)[-1] == '.fif':
return read_bem_surfaces(fname, on_defects='warn')[0]
else:
return _read_mri_surface(fname)
raise IOError('No head surface found for subject '
f'{subject} after trying:\n' + '\n'.join(try_fnames))
@verbose
def _get_skull_surface(surf, subject, subjects_dir, bem=None, verbose=None):
"""Get a skull surface from the Freesurfer subject directory.
Parameters
----------
surf : str
The name of the surface 'outer' or 'inner'.
%(subject)s
%(subjects_dir)s
bem : mne.bem.ConductorModel | None
The conductor model that stores information about the skull surface.
%(verbose)s
Returns
-------
skull_surf : dict | None
A dictionary with keys 'rr', 'tris', 'ntri', 'use_tris', 'np'
and 'coord_frame' that store information for mesh plotting and other
useful information about the head surface.
Notes
-----
.. versionadded: 0.24
"""
if bem is not None:
try:
return _bem_find_surface(bem, surf + '_skull')
except RuntimeError:
logger.info('Could not find the surface for '
'skull in the provided BEM model, '
'looking in the subject directory.')
subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
fname = _check_fname(op.join(subjects_dir, subject, 'bem',
surf + '_skull.surf'),
overwrite='read', must_exist=True,
name=f'{surf} skull surface')
return _read_mri_surface(fname)