def skeletonize_both():
from dipy.viz import fos
from dipy.core.track_metrics import downsample
from dipy.core.track_performance import local_skeleton_clustering, most_similar_track_mam
froi='/home/eg309/Data/ICBM_Wmpm/ICBM_WMPM.nii'
wI=get_roi(froi,9,0) #4 is genu
fname='/home/eg309/Data/PROC_MR10032/subj_03/101/1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_QA_warp.dpy'
#fname='/home/eg309/Data/PROC_MR10032/subj_03/101/1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_QA_native.dpy'
#fname='/home/eg309/Data/PROC_MR10032/subj_06/101/13122110752323511930000010092916083910900000227ep2dadvdiffDSI10125x25x25STs004a001_QA_native.dpy'
fname2='/home/eg309/Data/PROC_MR10032/subj_06/101/13122110752323511930000010092916083910900000227ep2dadvdiffDSI10125x25x25STs004a001_QA_warp.dpy'
r=fos.ren()
#'''
dpr=Dpy(fname,'r')
T=dpr.read_indexed(range(2*10**4))
dpr.close()
print len(T)
Td=[downsample(t,3) for t in T if length(t)>40]
C=local_skeleton_clustering(Td,d_thr=20.)
for c in C:
#color=np.random.rand(3)
color=fos.red
if C[c]['N']>0:
Ttmp=[]
for i in C[c]['indices']:
Ttmp.append(T[i])
si,s=most_similar_track_mam(Ttmp,'avg')
print si,C[c]['N']
fos.add(r,fos.line(Ttmp[si],color))
dpr=Dpy(fname2,'r')
T=dpr.read_indexed(range(2*10**4))
dpr.close()
print len(T)
Td=[downsample(t,3) for t in T if length(t)>40]
C=local_skeleton_clustering(Td,d_thr=20.)
#r=fos.ren()
for c in C:
#color=np.random.rand(3)
color=fos.yellow
if C[c]['N']>0:
Ttmp=[]
for i in C[c]['indices']:
Ttmp.append(T[i])
si,s=most_similar_track_mam(Ttmp,'avg')
print si,C[c]['N']
fos.add(r,fos.line(Ttmp[si],color))
#'''
fos.add(r,fos.point(wI,fos.green))
fos.show(r)
def test_picking_trajectories():
curves=[100*np.random.rand(10,3),100*np.random.rand(5,3),100*np.random.rand(3,3)]
curves=[100*np.array([[0,0,0],[1,0,0]]), 100*np.array([[0,1,0],[0,1,3]]),100*np.array([[0,2,0],[0,2,3]])]
'''
from nibabel import trackvis as tv
#fname='/home/eg309/Data/PROC_MR10032/subj_01/101/1312211075232351192010091419011391228126452ep2dadvdiffDSI25x25x25b4000s003a001_FA_warp.trk'
fname='/home/eg309/Data/fibers.trk'
streams,hdr=tv.read(fname)
T=[s[0] for s in streams]
curves=T[:200000]
'''
fname='/home/eg309/Data/PROC_MR10032/subj_02/101/1312211075232351192010091708112071055601107ep2dadvdiffDSI10125x25x25STs002a001_QA_native.dpy'
from dipy.io.dpy import Dpy
dpr=Dpy(fname,'r')
T=dpr.read_indexed(range(20000))
from dipy.core.track_metrics import length
curves=[t for t in T if length(t) > 20]
dpr.close()
#colors=np.random.rand(len(curves),4).astype('f4')
colors=0.5*np.ones((len(curves),4)).astype('f4')
for (i,c) in enumerate(curves):
orient=c[0]-c[-1]
orient=np.abs(orient/np.linalg.norm(orient))
colors[i,:3]=orient
c=InteractiveCurves(curves,colors=colors)
w=World()
w.add(c)
wi=Window()
wi.attach(w)
def tracks_in_roi():
froi='/home/eg309/Data/ICBM_Wmpm/ICBM_WMPM.nii'
wI=get_roi(froi,35,1) #4 is genu
fname='/home/eg309/Data/PROC_MR10032/subj_03/101/1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_QA_warp.dpy'
dpr=Dpy(fname,'r')
T=dpr.read_indexed(range(2*10**4))
print len(T)
Troi=[]
for t in T:
if track_roi_intersection_check(t,wI,.5):
Troi.append(t)
print(len(Troi))
dpr.close()
from dipy.viz import fos
r=fos.ren()
fos.add(r,fos.line(Troi,fos.red))
fos.add(r,fos.point(wI,fos.green))
fos.show(r)
def skeletonize():
froi='/home/eg309/Data/ICBM_Wmpm/ICBM_WMPM.nii'
wI=get_roi(froi,35,1) #4 is genu
#fname='/home/eg309/Data/PROC_MR10032/subj_03/101/1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_QA_warp.dpy'
#fname='/home/eg309/Data/PROC_MR10032/subj_03/101/1312211075232351192010092217244332311282470ep2dadvdiffDSI10125x25x25STs004a001_QA_native.dpy'
#fname='/home/eg309/Data/PROC_MR10032/subj_06/101/13122110752323511930000010092916083910900000227ep2dadvdiffDSI10125x25x25STs004a001_QA_native.dpy'
fname='/home/eg309/Data/PROC_MR10032/subj_06/101/13122110752323511930000010092916083910900000227ep2dadvdiffDSI10125x25x25STs004a001_QA_warp.dpy'
dpr=Dpy(fname,'r')
T=dpr.read_indexed(range(2*10**4))
dpr.close()
print len(T)
from dipy.core.track_metrics import downsample
from dipy.core.track_performance import local_skeleton_clustering, most_similar_track_mam
Td=[downsample(t,3) for t in T]
C=local_skeleton_clustering(Td,d_thr=20.)
#Tobject=np.array(T,dtype=np.object)
from dipy.viz import fos
r=fos.ren()
#skeleton=[]
for c in C:
color=np.random.rand(3)
if C[c]['N']>0:
Ttmp=[]
for i in C[c]['indices']:
Ttmp.append(T[i])
si,s=most_similar_track_mam(Ttmp,'avg')
print si,C[c]['N']
fos.add(r,fos.line(Ttmp[si],color))
#print len(skeleton)
#fos.add(r,fos.line(skeleton,color))
#fos.add(r,fos.line(T,fos.red))
fos.show(r)
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)
fdis=d101+'1312211075232351192010092912092080924175865ep2dadvdiffDSI10125x25x25STs005a001_nonlin_displacements.nii.gz'
ffareg=d101+'1312211075232351192010092912092080924175865ep2dadvdiffDSI10125x25x25STs005a001_bet_FA_reg.nii.gz'
flirtaff=d101+'1312211075232351192010092912092080924175865ep2dadvdiffDSI10125x25x25STs005a001_affine_transf.mat'
ftrack=d101+'1312211075232351192010092912092080924175865ep2dadvdiffDSI10125x25x25STs005a001_QA_native.dpy'
froi='/home/eg309/Data/PROC_MR10032/NIFTI_ROIs/AnatomicalROIs/ROI01_GCC.nii'
froi2='/home/eg309/Data/PROC_MR10032/NIFTI_ROIs/AnatomicalROIs/ROI02_BCC.nii'
#froi3='/home/eg309/Data/PROC_MR10032/NIFTI_ROIs/AnatomicalROIs/ROI03_SCC.nii'
froi3='/home/eg309/Downloads/SCC_analyze.nii'
ref_fname = '/usr/share/fsl/data/standard/FMRIB58_FA_1mm.nii.gz'
dpr=Dpy(ftrack,'r')
print dpr.track_no
T=dpr.read_indexed([0,1,2,3,2000,1000000])
for t in T:
print t.shape
dpr.close()
track=T[4]
im2im = flirt2aff_files(flirtaff, ffa, ref_fname) #ref_name to be replaced by ffareg
print im2im
from dipy.core.track_metrics import length
print len(track)
print length(track)
#ntrack=np.dot(im2im[:3,:3],track.T)+im2im[:3,[3]]
ntrack=np.dot(track,im2im[:3,:3].T)+im2im[:3,3]
print length(ntrack)
#print length(ntrack.T)
print length(ntrack)/length(track)
fdis=d101+'1312211075232351192010092912092080924175865ep2dadvdiffDSI10125x25x25STs005a001_nonlin_displacements.nii.gz'
ffareg=d101+'1312211075232351192010092912092080924175865ep2dadvdiffDSI10125x25x25STs005a001_bet_FA_reg.nii.gz'
flirtaff=d101+'1312211075232351192010092912092080924175865ep2dadvdiffDSI10125x25x25STs005a001_affine_transf.mat'
ftrack=d101+'1312211075232351192010092912092080924175865ep2dadvdiffDSI10125x25x25STs005a001_QA_native.dpy'
froi='/home/eg309/Data/PROC_MR10032/NIFTI_ROIs/AnatomicalROIs/ROI01_GCC.nii'
froi2='/home/eg309/Data/PROC_MR10032/NIFTI_ROIs/AnatomicalROIs/ROI02_BCC.nii'
#froi3='/home/eg309/Data/PROC_MR10032/NIFTI_ROIs/AnatomicalROIs/ROI03_SCC.nii'
froi3='/home/eg309/Downloads/SCC_analyze.nii'
ref_fname = '/usr/share/fsl/data/standard/FMRIB58_FA_1mm.nii.gz'
dpr=Dpy(ftrack,'r')
print dpr.track_no
T=dpr.read_indexed([0,1,2,3,2000,1000000])
for t in T:
print t.shape
dpr.close()
track=T[4]
im2im = flirt2aff_files(flirtaff, ffa, ref_fname) #ref_name to be replaced by ffareg
print im2im
from dipy.core.track_metrics import length
print len(track)
print length(track)
#ntrack=np.dot(im2im[:3,:3],track.T)+im2im[:3,[3]]
ntrack=np.dot(track,im2im[:3,:3].T)+im2im[:3,3]
print length(ntrack)
#print length(ntrack.T)
print length(ntrack)/length(track)
