def align(self, inp, ref, xfm):
"""
Aligns two images and stores the transform between them
**Positional Arguments:**
inp:
- Input impage to be aligned as a nifti image file
ref:
- Image being aligned to as a nifti image file
xfm:
- Returned transform between two images
"""
cmd = "flirt -in " + inp + " -ref " + ref + " -omat " + xfm +\
" -cost mutualinfo -bins 256 -dof 12 -searchrx -180 180" +\
" -searchry -180 180 -searchrz -180 180"
print("Executing: " + cmd)
mgu().execute_cmd(cmd)
pass
def align(self, inp, ref, xfm):
"""
Aligns two images and stores the transform between them
**Positional Arguments:**
inp:
- Input impage to be aligned as a nifti image file
ref:
- Image being aligned to as a nifti image file
xfm:
- Returned transform between two images
"""
cmd = "flirt -in " + inp + " -ref " + ref + " -omat " + xfm +\
" -cost mutualinfo -bins 256 -dof 12 -searchrx -180 180" +\
" -searchry -180 180 -searchrz -180 180"
print("Executing: " + cmd)
mgu().execute_cmd(cmd)
pass
def applyxfm(self, inp, ref, xfm, aligned):
"""
Aligns two images with a given transform
**Positional Arguments:**
inp:
- Input impage to be aligned as a nifti image file
ref:
- Image being aligned to as a nifti image file
xfm:
- Transform between two images
aligned:
- Aligned output image as a nifti image file
"""
cmd = "".join(["flirt -in ", inp, " -ref ", ref, " -out ", aligned,
" -init ", xfm, " -interp trilinear -applyxfm"])
print("Executing: " + cmd)
mgu().execute_cmd(cmd)
pass
def applyxfm(self, inp, ref, xfm, aligned):
"""
Aligns two images with a given transform
**Positional Arguments:**
inp:
- Input impage to be aligned as a nifti image file
ref:
- Image being aligned to as a nifti image file
xfm:
- Transform between two images
aligned:
- Aligned output image as a nifti image file
"""
cmd = "".join([
"flirt -in ", inp, " -ref ", ref, " -out ", aligned, " -init ",
xfm, " -interp trilinear -applyxfm"
])
print("Executing: " + cmd)
mgu().execute_cmd(cmd)
pass
def align_slices(self, dti, corrected_dti, idx):
"""
Performs eddy-correction (or self-alignment) of a stack of 3D images
**Positional Arguments:**
dti:
- 4D (DTI) image volume as a nifti file
corrected_dti:
- Corrected and aligned DTI volume in a nifti file
idx:
- Index of the first B0 volume in the stack
"""
cmd = "eddy_correct " + dti + " " + corrected_dti + " " + str(idx)
print("Executing: " + cmd)
status = mgu().execute_cmd(cmd)
pass
def align_slices(self, dti, corrected_dti, idx):
"""
Performs eddy-correction (or self-alignment) of a stack of 3D images
**Positional Arguments:**
dti:
- 4D (DTI) image volume as a nifti file
corrected_dti:
- Corrected and aligned DTI volume in a nifti file
idx:
- Index of the first B0 volume in the stack
"""
cmd = "eddy_correct " + dti + " " + corrected_dti + " " + str(idx)
print("Executing: " + cmd)
status = mgu().execute_cmd(cmd)
pass
def dti2atlas(self, dti, gtab, mprage, atlas,
aligned_dti, outdir, clean=False):
"""
Aligns two images and stores the transform between them
**Positional Arguments:**
dti:
- Input impage to be aligned as a nifti image file
bvals:
- File containing list of bvalues for each scan
bvecs:
- File containing gradient directions for each scan
mprage:
- Intermediate image being aligned to as a nifti image file
atlas:
- Terminal image being aligned to as a nifti image file
aligned_dti:
- Aligned output dti image as a nifti image file
"""
# Creates names for all intermediate files used
dti_name = mgu().get_filename(dti)
mprage_name = mgu().get_filename(mprage)
atlas_name = mgu().get_filename(atlas)
dti2 = mgu().name_tmps(outdir, dti_name, "_t2.nii.gz")
temp_aligned = mgu().name_tmps(outdir, dti_name, "_ta.nii.gz")
temp_aligned2 = mgu().name_tmps(outdir, dti_name, "_ta2.nii.gz")
b0 = mgu().name_tmps(outdir, dti_name, "_b0.nii.gz")
mprage2 = mgu().name_tmps(outdir, mprage_name, "_ss.nii.gz")
xfm = mgu().name_tmps(outdir, mprage_name,
"_" + atlas_name + "_xfm.mat")
# Align DTI volumes to each other
self.align_slices(dti, dti2, np.where(gtab.b0s_mask)[0])
# Loads DTI image in as data and extracts B0 volume
dti_im = nb.load(dti2)
b0_im = mgu().get_b0(gtab, dti_im.get_data())
# Wraps B0 volume in new nifti image
b0_head = dti_im.get_header()
b0_head.set_data_shape(b0_head.get_data_shape()[0:3])
b0_out = nb.Nifti1Image(b0_im, affine=dti_im.get_affine(),
header=b0_head)
b0_out.update_header()
nb.save(b0_out, b0)
# Applies skull stripping to MPRAGE volume
cmd = 'bet ' + mprage + ' ' + mprage2 + ' -B'
print("Executing: " + cmd)
mgu().execute_cmd(cmd)
# Algins B0 volume to MPRAGE, and MPRAGE to Atlas
cmd = "".join(['epi_reg --epi=', dti2, ' --t1=', mprage,
' --t1brain=', mprage2, ' --out=', temp_aligned])
print("Executing: " + cmd)
mgu().execute_cmd(cmd)
self.align(mprage, atlas, xfm)
# Applies combined transform to dti image volume
self.applyxfm(temp_aligned, atlas, xfm, temp_aligned2)
self.resample(temp_aligned2, aligned_dti, atlas)
if clean:
cmd = "".join(["rm -f ", dti2, " ", temp_aligned,
" ", b0, " ", xfm, " ", outdir, "/tmp/",
mprage_name, "*"])
print("Cleaning temporary registration files...")
mgu().execute_cmd(cmd)
def dti2atlas(self,
dti,
gtab,
mprage,
atlas,
aligned_dti,
outdir,
clean=False):
"""
Aligns two images and stores the transform between them
**Positional Arguments:**
dti:
- Input impage to be aligned as a nifti image file
bvals:
- File containing list of bvalues for each scan
bvecs:
- File containing gradient directions for each scan
mprage:
- Intermediate image being aligned to as a nifti image file
atlas:
- Terminal image being aligned to as a nifti image file
aligned_dti:
- Aligned output dti image as a nifti image file
"""
# Creates names for all intermediate files used
dti_name = mgu().get_filename(dti)
mprage_name = mgu().get_filename(mprage)
atlas_name = mgu().get_filename(atlas)
dti2 = mgu().name_tmps(outdir, dti_name, "_t2.nii.gz")
temp_aligned = mgu().name_tmps(outdir, dti_name, "_ta.nii.gz")
temp_aligned2 = mgu().name_tmps(outdir, dti_name, "_ta2.nii.gz")
b0 = mgu().name_tmps(outdir, dti_name, "_b0.nii.gz")
mprage2 = mgu().name_tmps(outdir, mprage_name, "_ss.nii.gz")
xfm = mgu().name_tmps(outdir, mprage_name,
"_" + atlas_name + "_xfm.mat")
# Align DTI volumes to each other
self.align_slices(dti, dti2, np.where(gtab.b0s_mask)[0][0])
# Loads DTI image in as data and extracts B0 volume
dti_im = nb.load(dti2)
b0_im = mgu().get_b0(gtab, dti_im.get_data())
# Wraps B0 volume in new nifti image
b0_head = dti_im.get_header()
b0_head.set_data_shape(b0_head.get_data_shape()[0:3])
b0_out = nb.Nifti1Image(b0_im,
affine=dti_im.get_affine(),
header=b0_head)
b0_out.update_header()
nb.save(b0_out, b0)
# Applies skull stripping to MPRAGE volume
cmd = 'bet ' + mprage + ' ' + mprage2 + ' -B'
print("Executing: " + cmd)
mgu().execute_cmd(cmd)
# Algins B0 volume to MPRAGE, and MPRAGE to Atlas
cmd = "".join([
'epi_reg --epi=', dti2, ' --t1=', mprage, ' --t1brain=', mprage2,
' --out=', temp_aligned
])
print("Executing: " + cmd)
mgu().execute_cmd(cmd)
self.align(mprage, atlas, xfm)
# Applies combined transform to dti image volume
self.applyxfm(temp_aligned, atlas, xfm, temp_aligned2)
self.resample(temp_aligned2, aligned_dti, atlas)
if clean:
cmd = "".join([
"rm -f ", dti2, " ", temp_aligned, " ", b0, " ", xfm, " ",
outdir, "/tmp/", mprage_name, "*"
])
print("Cleaning temporary registration files...")
mgu().execute_cmd(cmd)
