Beispiel #1
0
def show():    

    #brains=[(1,1),(1,2),(2,1),(3,1),(3,2)]
    brains=[(1,1),(2,1),(3,1)]

    ids=tl.emi_atlas()    
    
    #print ids.keys()
    
    for (b,s) in brains:
        
        ids2 = pbc.load_pickle(path+'/Relabelling_8_sc1_'+str(b)+'_'+str(s)+'.pkl')
        #'/Relabelling_8_sc1_'+str(b)+'_'+str(s)+'.pkl'
        print b,s, ids2.keys()
        tracks = pbc.load_approximate_tracks(path,b,s)
        
        for i in ids:
            
            if i >0:
                
                r=fos.ren()
                
                color=np.array(ids[i]['color'])                
                indices=ids2[i]['indices']                
                
                bundle=[tracks[ind] for ind in indices]      
                fos.add(r,fos.line(bundle,color,opacity=0.9))      
                
                print 'Bundle_name',i,ids[i]['bundle_name']            
                
                fos.show(r,title=ids[i]['bundle_name'][0])
def show_rep3(C,r=None,color=fos.white):

    if r==None: r=fos.ren()

    for c in C:
        fos.add(r,fos.line(C[c]['rep3']/C[c]['N'],color))

    fos.show(r)

    return r
Beispiel #3
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def show_rep3(C, r=None, color=fos.white):

    if r == None: r = fos.ren()

    for c in C:
        fos.add(r, fos.line(C[c]['rep3'] / C[c]['N'], color))

    fos.show(r)

    return r
Beispiel #4
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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)
Beispiel #5
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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)
Beispiel #6
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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)
Beispiel #7
0
        
r=fos.ren()

#fos.add(r,fos.line(tracks1,fos.red,opacity=0.01))
#fos.add(r,fos.line(tracks2,fos.cyan,opacity=0.01))

tracks1zshift=[t+np.array([-70,0,0]) for t in tracks1z]
tracks2zshift=[t+np.array([70,0,0]) for t in tracks2z]
tracks3zshift=[t+np.array([210,0,0]) for t in tracks3z]

fos.add(r,fos.line(tracks1zshift,fos.red,opacity=0.02))
fos.add(r,fos.line(tracks2zshift,fos.cyan,opacity=0.02))
fos.add(r,fos.line(tracks3zshift,fos.blue,opacity=0.02))

print 'Show track to track correspondence br1 br2'
for i in track2track:
	fos.add(r,fos.line(tracks1zshift[i[1]],fos.yellow,opacity=0.5,linewidth=3))
	fos.label(r,str(i[0]),tracks1zshift[i[1]][0],(4,4,4),fos.white)

	fos.add(r,fos.line(tracks2zshift[i[2]],fos.yellow,opacity=0.5,linewidth=3))
	fos.label(r,str(i[0]),tracks2zshift[i[2]][0],(4,4,4),fos.white)

print 'Show track to track correspondence br1_FACT and br2_RK2'
for i in track2track2:
	fos.add(r,fos.line(tracks3zshift[i[2]],fos.yellow,opacity=0.5,linewidth=3))
	fos.label(r,str(i[0]),tracks3zshift[i[2]][0],(4,4,4),fos.white)

fos.show(r,size=(1024,768))


Beispiel #8
0
r = fos.ren()
fos.add(r, fos.line(tracks, fos.red))
#fos.show(r)

for c in C:
    color = np.random.rand(3)
    for i in C[c]['indices']:
        fos.add(r, fos.line(tracks[i] + np.array([8., 0., 0.]), color))
        fos.add(r, fos.line(tracks[i] + np.array([16., 0., 0.]), color))

    fos.add(
        r,
        fos.line(C[c]['rep3'] / C[c]['N'] + np.array([16., 0., 0.]),
                 fos.white))

fos.show(r)
'''

print len(C)

C=pf.larch_3merge(C,0.5)

print len(C)

for c in C:
    color=np.random.rand(3)
    for i in C[c]['indices']:
        fos.add(r,fos.line(tracks[i]+np.array([14.,0.,0.]),color))
#fos.show(r)

for c in C:    
Beispiel #9
0
def plot_sphere(v, key):
    r = fos.ren()
    fos.add(r, fos.point(v, fos.green, point_radius=0.01))
    fos.show(r, title=key, size=(1000, 1000))
Beispiel #10
0
def plot_sphere(v,key):
    r = fos.ren()
    fos.add(r,fos.point(v,fos.green, point_radius= 0.01))
    fos.show(r, title=key, size=(1000,1000))
Beispiel #11
0
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)
Beispiel #12
0
r = fos.ren()
fos.add(r, fos.line(tracks, fos.red))
#fos.show(r)

for c in C:
    color = np.random.rand(3)
    for i in C[c]['indices']:
        fos.add(r, fos.line(tracks[i] + np.array([8., 0., 0.]), color))
        fos.add(r, fos.line(tracks[i] + np.array([16., 0., 0.]), color))

    fos.add(
        r,
        fos.line(C[c]['rep3'] / C[c]['N'] + np.array([16., 0., 0.]),
                 fos.white))

fos.show(r)
"""

print len(C)

C=pf.larch_3merge(C,0.5)

print len(C)

for c in C:
    color=np.random.rand(3)
    for i in C[c]['indices']:
        fos.add(r,fos.line(tracks[i]+np.array([14.,0.,0.]),color))
#fos.show(r)

for c in C:    
Beispiel #13
0
along = reference[index+1]-reference[index]
import numpy as np
normal=along/np.sqrt(np.inner(along,along))
crossings = list([])
hit_div = list([])
for k in range(len(b1)):
    t = b1[k]
    cross= -1
    for i in range(len(t))[:-1]:
        q = t[i]
        r = t[i+1]
        if np.inner(normal,q-p)*np.inner(normal,r-p) <= 0:
#            print "Segment %d of track %d crosses the normal plane" % (i,k)
            cross = i
            crossings.append([k,cross])
            if np.inner((r-q),normal) != 0:
                alpha = np.inner((p-q),normal)/np.inner((r-q),normal)
                hit = q+alpha*(r-q)
                divergence = (r-q)-np.inner(r-q,normal)*normal
                hit_div.append([hit,divergence])
            else:
                hit_div.append([hit,0])
            break
#    if cross<0:
#        print "No crossing segment"
#    if cross >= 0:
print "%d tracks cross the plane" % (len(crossings))
r = fos.ren()
fos.add(r,fos.points(np.array([h[0] for h in hit_div])))
fos.show()
Beispiel #14
0
C=pf.larch_3split(tracks,None,0.5)

r=fos.ren()
fos.add(r,fos.line(tracks,fos.red))
#fos.show(r)

for c in C:
    color=np.random.rand(3)
    for i in C[c]['indices']:
        fos.add(r,fos.line(tracks[i]+np.array([8.,0.,0.]),color))
        fos.add(r,fos.line(tracks[i]+np.array([16.,0.,0.]),color))

    fos.add(r,fos.line(C[c]['rep3']/C[c]['N']+np.array([16.,0.,0.]),fos.white))
        
    
fos.show(r)

"""

print len(C)

C=pf.larch_3merge(C,0.5)

print len(C)

for c in C:
    color=np.random.rand(3)
    for i in C[c]['indices']:
        fos.add(r,fos.line(tracks[i]+np.array([14.,0.,0.]),color))
#fos.show(r)
Beispiel #15
0
C=pf.larch_3split(tracks,None,0.5)

r=fos.ren()
fos.add(r,fos.line(tracks,fos.red))
#fos.show(r)

for c in C:
    color=np.random.rand(3)
    for i in C[c]['indices']:
        fos.add(r,fos.line(tracks[i]+np.array([8.,0.,0.]),color))
        fos.add(r,fos.line(tracks[i]+np.array([16.,0.,0.]),color))

    fos.add(r,fos.line(C[c]['rep3']/C[c]['N']+np.array([16.,0.,0.]),fos.white))
        
    
fos.show(r)

'''

print len(C)

C=pf.larch_3merge(C,0.5)

print len(C)

for c in C:
    color=np.random.rand(3)
    for i in C[c]['indices']:
        fos.add(r,fos.line(tracks[i]+np.array([14.,0.,0.]),color))
#fos.show(r)
Beispiel #16
0
print 'Deleting unnecessary data...'
del streams,hdr

print 'Hidden Structure Clustering...'
now=time.clock()
C=pf.local_skeleton_clustering(tracks,d_thr=20)
print 'Done in', time.clock()-now,'s.'

print 'Reducing the number of points...'
T=[pf.approximate_ei_trajectory(t) for t in T]

print 'Showing initial dataset.'
r=fos.ren()
fos.add(r,fos.line(T,fos.white,opacity=0.1))
fos.show(r)

print 'Showing dataset after clustering.'
fos.clear(r)
colors=np.zeros((len(T),3))
for c in C:
    color=np.random.rand(1,3)
    for i in C[c]['indices']:
        colors[i]=color
fos.add(r,fos.line(T,colors,opacity=1))
fos.show(r)

print 'Some statistics about the clusters'
lens=[len(C[c]['indices']) for c in C]
print 'max ',max(lens), 'min ',min(lens)
print 'singletons ',lens.count(1)
    #C=pf.local_skeleton_clustering(tracks,20.)
    print 'Done in total of ', time.clock() - tim, 'seconds.'

    print 'Saving result...'
    pkl.save_pickle(C_fname, C)

    streams = [(i, None, None) for i in atracks]
    tv.write(appr_fname, streams, hdr)

else:

    print 'Loading result...'
    C = pkl.load_pickle(C_fname)

skel = []
for c in C:

    skel.append(C[c]['repz'])

print 'Showing dataset after clustering...'
r = fos.ren()
fos.clear(r)
colors = np.zeros((len(skel), 3))
for (i, s) in enumerate(skel):

    color = np.random.rand(1, 3)
    colors[i] = color

fos.add(r, fos.line(skel, colors, opacity=1))
fos.show(r)
Beispiel #18
0
def showline(myline):
    from dipy.viz import fos
    r = fos.ren()
    fos.add(r,fos.line(myline,fos.blue,opacity=0.5))
    fos.show(r)