def test_invwarp():
base_dir = str(Path(__file__).parent / "examples")
anat_dir = f"{base_dir}/003/anat"
ref = f"{anat_dir}/sub-003_T1w.nii.gz"
warp = f"{anat_dir}/highres2standard_warp"
out = f"{anat_dir}/highres2standard_warp_inv.nii.gz"
utils.inverse_warp(ref, out, warp)
out_warp = nib.load(out)
assert out_warp is not None
def test_invwarp():
base_dir = os.path.abspath(
pkg_resources.resource_filename("pynets", "../data/examples"))
anat_dir = f"{base_dir}/003/anat"
ref = f"{anat_dir}/sub-003_T1w.nii.gz"
warp = f"{anat_dir}/highres2standard_warp"
out = f"{anat_dir}/highres2standard_warp_inv.nii.gz"
utils.inverse_warp(ref, out, warp)
out_warp = nib.load(out)
assert out_warp is not None
def t1w2mni_align(self):
"""
A function to perform alignment from T1w --> MNI template.
"""
import time
# Create linear transform/ initializer T1w-->MNI
regutils.align(
self.t1w_brain,
self.input_mni_brain,
xfm=self.t12mni_xfm_init,
bins=None,
interp="spline",
out=None,
dof=12,
cost="mutualinfo",
searchrad=True,
)
time.sleep(0.5)
# Attempt non-linear registration of T1 to MNI template
if self.simple is False:
try:
print(f"Learning a non-linear mapping from T1w --> "
f"{self.template_name} ...")
# Use FNIRT to nonlinearly align T1 to MNI template
regutils.align_nonlinear(
self.t1w_brain,
self.input_mni,
xfm=self.t12mni_xfm_init,
out=self.t1_aligned_mni,
warp=self.warp_t1w2mni,
ref_mask=self.input_mni_mask,
)
time.sleep(0.5)
# Get warp from MNI -> T1
regutils.inverse_warp(self.t1w_brain, self.mni2t1w_warp,
self.warp_t1w2mni)
time.sleep(0.5)
# Get mat from MNI -> T1
self.mni2t1_xfm = regutils.invert_xfm(self.t12mni_xfm_init,
self.mni2t1_xfm)
time.sleep(0.5)
except BaseException:
# Falling back to linear registration
regutils.align(
self.t1w_brain,
self.input_mni_brain,
xfm=self.mni2t1_xfm,
init=self.t12mni_xfm_init,
bins=None,
dof=12,
cost="mutualinfo",
searchrad=True,
interp="spline",
out=self.t1_aligned_mni,
sch=None,
)
time.sleep(0.5)
# Get mat from MNI -> T1
self.mni2t1_xfm = regutils.invert_xfm(self.t12mni_xfm,
self.mni2t1_xfm)
time.sleep(0.5)
else:
# Falling back to linear registration
regutils.align(
self.t1w_brain,
self.input_mni_brain,
xfm=self.t12mni_xfm,
init=self.t12mni_xfm_init,
bins=None,
dof=12,
cost="mutualinfo",
searchrad=True,
interp="spline",
out=self.t1_aligned_mni,
sch=None,
)
time.sleep(0.5)
# Get mat from MNI -> T1
self.t12mni_xfm = regutils.invert_xfm(self.mni2t1_xfm,
self.t12mni_xfm)
time.sleep(0.5)