def tracks_to_fmrib58(subj,fnames,data_type='fa'):
#affine transformation matrix (from flirt before nonlinear registration)
faff =dname+fnames[subj]+'_affine_transf.mat'
#nonlinear displacements
fdis =dname+fnames[subj]+'_nonlin_displacements.nii.gz'#look at fa_to_fmrib58
if data_type=='qa':
#fqa_warp_dpy
fqa_warp =dname+fnames[subj]+'_QA_warp.dpy'
fwarp=fqa_warp
if data_type=='fa':
ffa_warp =dname+fnames[subj]+'_FA_warp.dpy'
fwarp=ffa_warp
#fa
ffa =dname+fnames[subj]+'_bet_FA.nii.gz'
ref_fname = '/usr/share/fsl/data/standard/FMRIB58_FA_1mm.nii.gz'
print faff
print ffa
print fdis
im2im = flirt2aff_files(faff, ffa, ref_fname)
dimg=ni.load(fdis)
daff=dimg.get_affine()
ddata=dimg.get_data()
di=ddata[:,:,:,0]#copy i
dj=ddata[:,:,:,1]#copy j
dk=ddata[:,:,:,2]#copy k
#WARP TRACKS IN BLOCKS
print fwarp
dprw=Dpy(fwarp,'r+')
rows=len(dprw.f.root.streamlines.tracks)
blocks=np.round(np.linspace(0,rows,20)).astype(int)#lets work in blocks
print rows
for i in range(len(blocks)-1):
print blocks[i],blocks[i+1]
caboodle=dprw.f.root.streamlines.tracks[blocks[i]:blocks[i+1]]
ntrack=np.dot(caboodle,im2im[:3,:3].T)+im2im[:3,3] #from image vox space to mni image vox
mci=mc(di,ntrack.T,order=1) #mapping for i
mcj=mc(dj,ntrack.T,order=1) #mapping for j
mck=mc(dk,ntrack.T,order=1) #mapping for k
wtrack=ntrack+np.vstack((mci,mcj,mck)).T
caboodlew=np.dot(wtrack,daff[:3,:3].T)+daff[:3,3]
dprw.f.root.streamlines.tracks[blocks[i]:blocks[i+1]]=caboodlew.astype('f4')
dprw.close()
def warp_reference_grid(flaff,fdis,fref,ffaw):
''' Warp reference space grid using fsl displacements
Parameters
----------
flaff: filename of .mat (flirt)
fdis: filename of displacements (fnirtfileutils)
fref: filename of reference volume e.g. (FMRIB58_FA_1mm.nii.gz)
Returns
-------
warped grid in reference index space
'''
refaff=nib.load(fref).get_affine()
disdata=nib.load(fdis).get_data()
#from fa index to ref index
res=flirt2aff_files(flaff,ffa,fref)
#create the 4d volume which has the indices for the reference image
refgrid=np.zeros(disdata.shape)
#create the grid indices for the reference
refgrid[...,0] = np.arange(disdata.shape[0])[:,newaxis,newaxis]
refgrid[...,1] = np.arange(disdata.shape[1])[newaxis,:,newaxis]
refgrid[...,2] = np.arange(disdata.shape[2])[newaxis,newaxis,:]
#hold the displacements' shape reshaping
di,dj,dk,dl=disdata.shape
N=di*dj*dk
warpedgrid=np.zeros(disdata.shape)
for l in range(dl):
warpedgrid[:,:,:,l]=mc(disdata[:,:,:,l].reshape(N,1),refgrid.reshape(N,dl).T,order=1).reshape(di,dj,dk)
warpedgrid = refgrid+np.dot(warpedgrid,res[:3,:3].T)+res[:3,3]
return refgrid, warpedgrid
def warp_displacements(ffa, flaff, fdis, fref, ffaw, order=1):
''' Warp an image using fsl displacements
Parameters
------------
ffa : filename of nifti to be warped
flaff : filename of .mat (flirt)
fdis : filename of displacements (fnirtfileutils)
fref : filename of reference volume e.g. (FMRIB58_FA_1mm.nii.gz)
ffaw : filename for the output warped image
'''
refaff = nib.load(fref).get_affine()
disdata = nib.load(fdis).get_data()
imgfa = nib.load(ffa)
fadata = imgfa.get_data()
fazooms = imgfa.get_header().get_zooms()
# from fa index to ref index
res = flirt2aff_files(flaff, ffa, fref)
# from ref index to fa index
ires = np.linalg.inv(res)
# create the 4d volume which has the indices for the reference image
reftmp = np.zeros(disdata.shape)
'''
#create the grid indices for the reference
#refinds = np.ndindex(disdata.shape[:3])
for ijk_t in refinds:
i,j,k = ijk_t
reftmp[i,j,k,0]=i
reftmp[i,j,k,1]=j
reftmp[i,j,k,2]=k
'''
# same as commented above but much faster
reftmp[..., 0] = np.arange(disdata.shape[0])[:, newaxis, newaxis]
reftmp[..., 1] = np.arange(disdata.shape[1])[newaxis, :, newaxis]
reftmp[..., 2] = np.arange(disdata.shape[2])[newaxis, newaxis, :]
# affine transform from reference index to the fa index
A = np.dot(reftmp, ires[:3, :3].T) + ires[:3, 3]
# add the displacements but first devide them by the voxel sizes
A2 = A + disdata / fazooms
# hold the displacements' shape reshaping
di, dj, dk, dl = disdata.shape
# do the interpolation using map coordinates
# the list of points where the interpolation is done given by the reshaped
# in 2D A2 (list of 3d points in fa index)
W = mc(fadata, A2.reshape(di * dj * dk, dl).T, order=order).reshape(di, dj,
dk)
# save the warped image
Wimg = nib.Nifti1Image(W, refaff)
nib.save(Wimg, ffaw)
def warp_displacements(ffa, flaff, fdis, fref, ffaw, order=1):
''' Warp an image using fsl displacements
Parameters
------------
ffa : filename of nifti to be warped
flaff : filename of .mat (flirt)
fdis : filename of displacements (fnirtfileutils)
fref : filename of reference volume e.g. (FMRIB58_FA_1mm.nii.gz)
ffaw : filename for the output warped image
'''
refaff = nib.load(fref).affine
disdata = nib.load(fdis).get_data()
imgfa = nib.load(ffa)
fadata = imgfa.get_data()
fazooms = imgfa.header.get_zooms()
# from fa index to ref index
res = flirt2aff_files(flaff, ffa, fref)
# from ref index to fa index
ires = np.linalg.inv(res)
# create the 4d volume which has the indices for the reference image
reftmp = np.zeros(disdata.shape)
'''
#create the grid indices for the reference
#refinds = np.ndindex(disdata.shape[:3])
for ijk_t in refinds:
i,j,k = ijk_t
reftmp[i,j,k,0]=i
reftmp[i,j,k,1]=j
reftmp[i,j,k,2]=k
'''
# same as commented above but much faster
reftmp[..., 0] = np.arange(disdata.shape[0])[:, newaxis, newaxis]
reftmp[..., 1] = np.arange(disdata.shape[1])[newaxis, :, newaxis]
reftmp[..., 2] = np.arange(disdata.shape[2])[newaxis, newaxis, :]
# affine transform from reference index to the fa index
A = np.dot(reftmp, ires[:3, :3].T) + ires[:3, 3]
# add the displacements but first devide them by the voxel sizes
A2 = A + disdata / fazooms
# hold the displacements' shape reshaping
di, dj, dk, dl = disdata.shape
# do the interpolation using map coordinates
# the list of points where the interpolation is done given by the reshaped
# in 2D A2 (list of 3d points in fa index)
W = mc(fadata, A2.reshape(di * dj * dk, dl).T, order=order).reshape(di, dj,
dk)
# save the warped image
Wimg = nib.Nifti1Image(W, refaff)
nib.save(Wimg, ffaw)
def warp_displacements_tracks(fdpy, ffa, fmat, finv, fdis, fdisa, fref, fdpyw):
""" Warp tracks from native space to the FMRIB58/MNI space
We use here the fsl displacements. Have a look at create_displacements to
see an example of how to use these displacements.
Parameters
------------
fdpy : filename of the .dpy file with the tractography
ffa : filename of nifti to be warped
fmat : filename of .mat (flirt)
fdis : filename of displacements (fnirtfileutils)
fdisa : filename of displacements (fnirtfileutils + affine)
finv : filename of invwarp displacements (invwarp)
fref : filename of reference volume e.g. (FMRIB58_FA_1mm.nii.gz)
fdpyw : filename of the warped tractography
See also
-----------
dipy.external.fsl.create_displacements
"""
# read the tracks from the image space
dpr = Dpy(fdpy, 'r')
T = dpr.read_tracks()
dpr.close()
# copy them in a new file
dpw = Dpy(fdpyw, 'w', compression=1)
dpw.write_tracks(T)
dpw.close()
# from fa index to ref index
res = flirt2aff_files(fmat, ffa, fref)
# load the reference img
imgref = nib.load(fref)
refaff = imgref.get_affine()
# load the invwarp displacements
imginvw = nib.load(finv)
invwdata = imginvw.get_data()
invwaff = imginvw.get_affine()
# load the forward displacements
imgdis = nib.load(fdis)
disdata = imgdis.get_data()
# load the forward displacements + affine
imgdis2 = nib.load(fdisa)
disdata2 = imgdis2.get_data()
# from their difference create the affine
disaff = disdata2 - disdata
del disdata
del disdata2
shape = nib.load(ffa).get_data().shape
# transform the displacements affine back to image space
disaff0 = affine_transform(disaff[..., 0], res[:3, :3], res[:3, 3], shape,
order=1)
disaff1 = affine_transform(disaff[..., 1], res[:3, :3], res[:3, 3], shape,
order=1)
disaff2 = affine_transform(disaff[..., 2], res[:3, :3], res[:3, 3], shape,
order=1)
# remove the transformed affine from the invwarp displacements
di = invwdata[:, :, :, 0] + disaff0
dj = invwdata[:, :, :, 1] + disaff1
dk = invwdata[:, :, :, 2] + disaff2
dprw = Dpy(fdpyw, 'r+')
rows = len(dprw.f.root.streamlines.tracks)
blocks = np.round(np.linspace(0, rows, 10)).astype(int) # lets work in
# blocks
# print rows
for i in range(len(blocks) - 1):
# print blocks[i],blocks[i+1]
# copy a lot of tracks together
caboodle = dprw.f.root.streamlines.tracks[blocks[i]:blocks[i + 1]]
mci = mc(di, caboodle.T, order=1) # interpolations for i displacement
mcj = mc(dj, caboodle.T, order=1) # interpolations for j displacement
mck = mc(dk, caboodle.T, order=1) # interpolations for k displacement
D = np.vstack((mci, mcj, mck)).T
# go back to mni image space
WI2 = np.dot(caboodle, res[:3, :3].T) + res[:3, 3] + D
# and then to mni world space
caboodlew = np.dot(WI2, refaff[:3, :3].T) + refaff[:3, 3]
# write back
dprw.f.root.streamlines.tracks[blocks[i]:blocks[i + 1]] = (
caboodlew.astype('f4'))
dprw.close()
def warp_displacements_tracks(fdpy, ffa, fmat, finv, fdis, fdisa, fref, fdpyw):
""" Warp tracks from native space to the FMRIB58/MNI space
We use here the fsl displacements. Have a look at create_displacements to
see an example of how to use these displacements.
Parameters
------------
fdpy : filename of the .dpy file with the tractography
ffa : filename of nifti to be warped
fmat : filename of .mat (flirt)
fdis : filename of displacements (fnirtfileutils)
fdisa : filename of displacements (fnirtfileutils + affine)
finv : filename of invwarp displacements (invwarp)
fref : filename of reference volume e.g. (FMRIB58_FA_1mm.nii.gz)
fdpyw : filename of the warped tractography
See also
-----------
dipy.external.fsl.create_displacements
"""
# read the tracks from the image space
dpr = Dpy(fdpy, 'r')
T = dpr.read_tracks()
dpr.close()
# copy them in a new file
dpw = Dpy(fdpyw, 'w', compression=1)
dpw.write_tracks(T)
dpw.close()
# from fa index to ref index
res = flirt2aff_files(fmat, ffa, fref)
# load the reference img
imgref = nib.load(fref)
refaff = imgref.affine
# load the invwarp displacements
imginvw = nib.load(finv)
invwdata = imginvw.get_data()
# load the forward displacements
imgdis = nib.load(fdis)
disdata = imgdis.get_data()
# load the forward displacements + affine
imgdis2 = nib.load(fdisa)
disdata2 = imgdis2.get_data()
# from their difference create the affine
disaff = disdata2 - disdata
del disdata
del disdata2
shape = nib.load(ffa).get_data().shape
# transform the displacements affine back to image space
disaff0 = affine_transform(disaff[..., 0], res[:3, :3], res[:3, 3], shape,
order=1)
disaff1 = affine_transform(disaff[..., 1], res[:3, :3], res[:3, 3], shape,
order=1)
disaff2 = affine_transform(disaff[..., 2], res[:3, :3], res[:3, 3], shape,
order=1)
# remove the transformed affine from the invwarp displacements
di = invwdata[:, :, :, 0] + disaff0
dj = invwdata[:, :, :, 1] + disaff1
dk = invwdata[:, :, :, 2] + disaff2
dprw = Dpy(fdpyw, 'r+')
rows = len(dprw.f.root.streamlines.tracks)
blocks = np.round(np.linspace(0, rows, 10)).astype(int) # lets work in
# blocks
# print rows
for i in range(len(blocks) - 1):
# print blocks[i],blocks[i+1]
# copy a lot of tracks together
caboodle = dprw.f.root.streamlines.tracks[blocks[i]:blocks[i + 1]]
mci = mc(di, caboodle.T, order=1) # interpolations for i displacement
mcj = mc(dj, caboodle.T, order=1) # interpolations for j displacement
mck = mc(dk, caboodle.T, order=1) # interpolations for k displacement
D = np.vstack((mci, mcj, mck)).T
# go back to mni image space
WI2 = np.dot(caboodle, res[:3, :3].T) + res[:3, 3] + D
# and then to mni world space
caboodlew = np.dot(WI2, refaff[:3, :3].T) + refaff[:3, 3]
# write back
dprw.f.root.streamlines.tracks[blocks[i]:blocks[i + 1]] = (
caboodlew.astype('f4'))
dprw.close()
def warp_tracks():
dn='/home/eg309/Data/TEST_MR10032/subj_03/101/'
ffa=dn+'1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_bet_FA.nii.gz'
finvw=dn+'1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_warps_in_bet_FA.nii.gz'
fqadpy=dn+'1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_QA_native.dpy'
flaff=dn+'1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_affine_transf.mat'
fref ='/usr/share/fsl/data/standard/FMRIB58_FA_1mm.nii.gz'
fdis =dn+'1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_nonlin_displacements.nii.gz'
fdis2 =dn+'1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_nonlin_displacements_withaff.nii.gz'
#read some tracks
dpr=Dpy(fqadpy,'r')
T=dpr.read_indexed(range(150))
dpr.close()
#from fa index to ref index
res=flirt2aff_files(flaff,ffa,fref)
#load the reference img
imgref=ni.load(fref)
refaff=imgref.get_affine()
#load the invwarp displacements
imginvw=ni.load(finvw)
invwdata=imginvw.get_data()
invwaff = imginvw.get_affine()
#load the forward displacements
imgdis=ni.load(fdis)
disdata=imgdis.get_data()
#load the forward displacements + affine
imgdis2=ni.load(fdis2)
disdata2=imgdis2.get_data()
#from their difference create the affine
disaff=imgdis2.get_data()-disdata
shift=np.array([disaff[...,0].mean(),disaff[...,1].mean(),disaff[...,2].mean()])
shape=ni.load(ffa).get_data().shape
disaff0=affine_transform(disaff[...,0],res[:3,:3],res[:3,3],shape,order=1)
disaff1=affine_transform(disaff[...,1],res[:3,:3],res[:3,3],shape,order=1)
disaff2=affine_transform(disaff[...,2],res[:3,:3],res[:3,3],shape,order=1)
disdata0=affine_transform(disdata[...,0],res[:3,:3],res[:3,3],shape,order=1)
disdata1=affine_transform(disdata[...,1],res[:3,:3],res[:3,3],shape,order=1)
disdata2=affine_transform(disdata[...,2],res[:3,:3],res[:3,3],shape,order=1)
#print disgrad0.shape,disgrad1.shape,disgrad2.shape
#disdiff=np.empty(invwdata.shape)
#disdiff[...,0]=disgrad0
#disdiff[...,1]=disgrad1
#disdiff[...,2]=disgrad2
#ni.save(ni.Nifti1Image(disdiff,invwaff),'/tmp/disdiff.nii.gz')
di=disdata0
dj=disdata1
dk=disdata2
d2i=invwdata[:,:,:,0] + disaff0
d2j=invwdata[:,:,:,1] + disaff1
d2k=invwdata[:,:,:,2] + disaff2
#di=disgrad0
#dj=disgrad1
#dk=disgrad2
imgfa=ni.load(ffa)
fadata=imgfa.get_data()
faaff =imgfa.get_affine()
Tw=[]
Tw2=[]
Tw3=[]
froi='/home/eg309/Data/ICBM_Wmpm/ICBM_WMPM.nii'
roiI=get_roi(froi,3,1) #3 is GCC
roiI2=get_roi(froi,4,1) #4 is BCC
roiI3=get_roi(froi,5,1) #4 is SCC
roiI=np.vstack((roiI,roiI2,roiI3))
for t in T:
if np.min(t[:,2])>=0:#to be removed
mci=mc(di,t.T,order=1) #interpolations for i displacement
mcj=mc(dj,t.T,order=1) #interpolations for j displacement
mck=mc(dk,t.T,order=1) #interpolations for k displacement
D=np.vstack((mci,mcj,mck)).T
WI=np.dot(t,res[:3,:3].T)+res[:3,3]+D#+ shift
W=np.dot(WI,refaff[:3,:3].T)+refaff[:3,3]
mc2i=mc(d2i,t.T,order=1) #interpolations for i displacement
mc2j=mc(d2j,t.T,order=1) #interpolations for j displacement
mc2k=mc(d2k,t.T,order=1) #interpolations for k displacement
D2=np.vstack((mc2i,mc2j,mc2k)).T
WI2=np.dot(t,res[:3,:3].T)+res[:3,3]+D2 #+ shift
W2=np.dot(WI2,refaff[:3,:3].T)+refaff[:3,3]
WI3=np.dot(t,res[:3,:3].T)+res[:3,3]
W3=np.dot(WI3,refaff[:3,:3].T)+refaff[:3,3]
Tw.append(W)
Tw2.append(W2)
Tw3.append(W3)
from dipy.viz import fos
r=fos.ren()
fos.add(r,fos.line(Tw,fos.red))
fos.add(r,fos.line(Tw2,fos.green))
fos.add(r,fos.line(Tw3,fos.yellow))
fos.add(r,fos.sphere((0,0,0),10,color=fos.blue))
fos.add(r,fos.point(roiI,fos.blue))
fos.show(r)
def DespoticCO32(Tvals,n):
intensity = mc(co32, [[fx(Tvals)],[fy(n)]])
return(intensity)
def DespoticCO21(Tvals,n):
intensity = mc(co21, [[fx(Tvals)],[fy(n)]])
return(intensity)
def DespoticCO10(Tvals,n):
intensity = mc(co10, [[fx(Tvals)],[fy(n)]])
return(intensity)
