def splitModels(self, Surface):
dataArray = Surface.GetPointData().GetScalars("GroupIds")
scalarRange = dataArray.GetRange()
newPdList = []
newCaList = []
self._parentClass._helper.debug("started splitter")
# generate containers CellArray & PolyData + copy points
for i in range(1, int(scalarRange[1]) + 2):
newCellArray = slicer.vtkCellArray()
newPolyData = slicer.vtkPolyData()
points = slicer.vtkPoints()
points.DeepCopy(Surface.GetPoints())
newPolyData.SetPoints(points)
newPolyData.SetPolys(newCellArray)
newPolyData.Update()
newPdList.append(newPolyData)
newCaList.append(newCellArray)
#Fill containers with Polys
for i in range(0, Surface.GetPolys().GetNumberOfCells()):
poi = Surface.GetCell(i).GetPointIds()
if (poi.GetNumberOfIds() == 0):
continue
scalarsOfPoints = []
for pid in range(0, poi.GetNumberOfIds()):
p = poi.GetId(pid)
scalarsOfPoints.append(dataArray.GetValue(p))
max = 0
largestIndex = 0
for j in range(1, int(scalarRange[1]) + 2):
c = scalarsOfPoints.count(j)
if c >= max:
max = c
largestIndex = j
newCaList[largestIndex].InsertNextCell(Surface.GetCell(i))
# clean PolyData
for pd in newPdList:
cleanPolyData = slicer.vtkCleanPolyData()
cleanPolyData.SetInput(pd)
cleanPolyData.Update()
pd.DeepCopy(cleanPolyData.GetOutput())
self._parentClass._helper.debug("finished splitter")
return newPdList
def splitModels(self,Surface):
dataArray=Surface.GetPointData().GetScalars("GroupIds")
scalarRange=dataArray.GetRange()
newPdList=[]
newCaList=[]
self._parentClass._helper.debug("started splitter")
# generate containers CellArray & PolyData + copy points
for i in range(1,int(scalarRange[1])+2):
newCellArray=slicer.vtkCellArray()
newPolyData=slicer.vtkPolyData()
points=slicer.vtkPoints()
points.DeepCopy(Surface.GetPoints())
newPolyData.SetPoints(points)
newPolyData.SetPolys(newCellArray)
newPolyData.Update()
newPdList.append(newPolyData)
newCaList.append(newCellArray)
#Fill containers with Polys
for i in range (0,Surface.GetPolys().GetNumberOfCells()):
poi=Surface.GetCell(i).GetPointIds()
if(poi.GetNumberOfIds()==0):
continue
scalarsOfPoints =[]
for pid in range(0,poi.GetNumberOfIds()):
p=poi.GetId(pid)
scalarsOfPoints.append(dataArray.GetValue(p))
max=0
largestIndex=0
for j in range(1,int(scalarRange[1])+2):
c=scalarsOfPoints.count(j)
if c >= max:
max=c
largestIndex=j
newCaList[largestIndex].InsertNextCell(Surface.GetCell(i))
# clean PolyData
for pd in newPdList:
cleanPolyData = slicer.vtkCleanPolyData();
cleanPolyData.SetInput(pd);
cleanPolyData.Update();
pd.DeepCopy(cleanPolyData.GetOutput())
self._parentClass._helper.debug("finished splitter")
return newPdList
def Execute(dwi_node, seeds_node, mask_node, ff_node, \
record_fa = False, record_state = False, record_cov = False, \
model="two-tensor", FA_min=.15, GA_min=.10,
seeds=1, labels=[1],
Qm=.0030, Ql=100, Rs=.015, theta_max=45):
for i in xrange(10):
print ''
is_2t = (model == "two-tensor")
print 'HACK hardcode 2T'
is_2t = True
follow = iff(is_2t, follow2t, follow1t)
state_dim = iff(is_2t, 10, 5) # dimension of state space
theta_min = 5 # angle which triggers branch
param = dict({
'FA_min': FA_min, # fractional anisotropy stopping threshold
'GA_min': GA_min, # generalized anisotropy stopping threshold
'dt': .2, # forward Euler step size (path integration)
'max_len': 250, # stop if fiber gets this long
'min_radius': .87, # stop if fiber curves this much
'seeds': seeds, # number of seeds in each voxel
'theta_min':
np.cos(theta_min * np.pi / 180), # angle which triggers branch
'theta_max':
np.cos(theta_max * np.pi / 180), # angle which triggers branch
'min_radius': .87, # stop if fiber curves this much
'record_fa': record_fa,
'record_st': record_state,
'record_co': record_cov,
# Kalman filter parameters
'Qm': Qm, # injected angular noise
'Ql': Ql, # injected eigenvalue noise
'Rs': Rs, # dependent on latent noise in your data
'P0': 0.01 * np.eye(state_dim)
}) # initial covariance
from Slicer import slicer
# foo = slicer.vtkFloatArray()
# foo.SetNumberOfComponents(1)
# foo.SetName('foo')
# foo.InsertNextValue(234) # Success
# foo.InsertNextValue(23.4) # Success
# foo.InsertNextValue(255 * np.random.rand()) # Success
# foo.InsertNextValue(np.empty(1,dtype='float32')) # FAIL
# foo.InsertNextValue(np.empty(1,dtype='float64')) # FAIL
# asdf
scene = slicer.MRMLScene
dwi_node = scene.GetNodeByID(dwi_node)
seeds_node = scene.GetNodeByID(seeds_node)
mask_node = scene.GetNodeByID(mask_node)
ff_node = scene.GetNodeByID(ff_node)
# ensure normalized signal
bb = dwi_node.GetBValues().ToArray()
if np.any(bb.sum(1) == 0):
import Slicer
Slicer.tk.eval(
'tk_messageBox -message "Use the \'Normalize Signal\' module to prepare the DWI data"'
)
return
b = bb.mean()
S = dwi_node.GetImageData().ToArray()
u = dwi_node.GetDiffusionGradients().ToArray()
i2r = vtk2mat(dwi_node.GetIJKToRASMatrix, slicer)
r2i = vtk2mat(dwi_node.GetRASToIJKMatrix, slicer)
mf = vtk2mat(dwi_node.GetMeasurementFrameMatrix, slicer)
voxel = np.mat(dwi_node.GetSpacing()).reshape(3, 1)
voxel = voxel[::-1] # HACK Numpy has [z y x]
# generalized loading...
R = r2i[0:3, 0:3] / voxel.T # normalize each column
M = mf[0:3, 0:3]
# transform gradients
u = dwi_node.GetDiffusionGradients().ToArray()
u = u * (np.linalg.inv(R) * M).T
u = u / np.sqrt(np.power(u, 2).sum(1))
u = np.vstack((u, -u)) # duplicate signal
param['voxel'] = voxel
mask = mask_node.GetImageData().ToArray().astype('uint16')
# pull all seeds
seeds_ = seeds_node.GetImageData().ToArray()
seeds = np.zeros(seeds_.shape, dtype='bool')
for lbl in labels:
seeds |= (seeds_ == lbl)
seeds = zip(*seeds.nonzero())
# ensure seeds
if len(seeds) == 0:
import Slicer
Slicer.tk.eval(
'tk_messageBox -message "No seeds found for this label"')
return
# double check branching
if 0 < theta_max and theta_max < 5:
import Slicer
Slicer.tk.eval(
'tk_messageBox -message "Nonzero branching angle must be greater than 5 degrees"'
)
return
is_branching = is_2t and param['theta_max'] < 1
# tractography...
ff1 = init(S, seeds, u, b, param, is_2t)
ff2, ff_fa, ff_st, ff_co = [], [], [], []
t1 = time.time()
for i in xrange(0, len(ff1)):
print '[%3.0f%%] (%7d - %7d)' % (100.0 * i / len(ff1), i, len(ff1))
ff1[i], next, extra = follow(S, u, b, mask, ff1[i], param,
is_branching)
ff2.extend(next)
# store extras
if record_fa: ff_fa.append(extra[0])
if record_state: ff_st.append(extra[1])
if record_cov: ff_co.append(extra[2])
t2 = time.time()
print 'Time: ', t2 - t1, 'sec'
if is_branching:
for i in xrange(0, len(ff2)):
print '[%3.0f%%] (%7d - %7d)' % (100.0 * i / len(ff2), i, len(ff2))
f, _ = follow(S, u, b, mask, ff2[i], param, False)
ff1.append(f)
print 'Time: ', time.time() - t2, 'sec'
# build polydata
ss_x = slicer.vtkPoints()
lines = slicer.vtkCellArray()
if record_fa:
ss_fa = slicer.vtkFloatArray()
ss_fa.SetNumberOfComponents(1)
ss_fa.SetName('FA')
if record_state:
ss_st = slicer.vtkFloatArray()
ss_st.SetNumberOfComponents(state_dim)
ss_st.SetName('state')
if record_cov:
ss_co = slicer.vtkFloatArray()
ss_co.SetNumberOfComponents(state_dim**2)
ss_co.SetName('covariance')
cell_id = 0
for i in xrange(0, len(ff1)):
f = ff1[i]
lines.InsertNextCell(len(f))
if record_fa: f_fa = ff_fa[i]
if record_state: f_st = ff_st[i]
if record_cov: f_co = ff_co[i]
for j in xrange(0, len(f)):
lines.InsertCellPoint(cell_id)
cell_id += 1
x = f[j]
x = x[::-1] # HACK
x_ = np.array(transform(i2r, x)).ravel() # HACK
ss_x.InsertNextPoint(x_[0], x_[1], x_[2])
if record_fa:
ss_fa.InsertNextValue(255 * f_fa[j]) # FIXME numpy type
if record_state: ss_st.InsertNextValue(f_fa[j]) # FIXME tuples?
if record_cov: ss_co.InsertNextValue(f_fa[j]) # FIXME tuples?
# setup output fibers
dnode = ff_node.GetDisplayNode()
if not dnode:
dnode = slicer.vtkMRMLModelDisplayNode()
ff_node.GetScene().AddNodeNoNotify(dnode)
ff_node.SetAndObserveDisplayNodeID(dnode.GetID())
pd = ff_node.GetPolyData()
if not pd:
pd = slicer.vtkPolyData() # create if necessary
ff_node.SetAndObservePolyData(pd)
pd.SetPoints(ss_x)
if record_fa: pd.GetPointData().SetScalars(ss_fa)
pd.SetLines(lines)
pd.Update()
ff_node.Modified()
asdf # HACK flush stdio
def Import(self):
outModel = self._importModelSelector.GetSelected()
outputFileName = self._loadButton.GetFileName()
if outModel and outputFileName:
self._helper.debug("Start import..")
points = slicer.vtkPoints()
conn = slicer.vtkCellArray()
polyData = slicer.vtkPolyData()
f=open(outputFileName)
lines = f.readlines()
i = 0
lastId = None
for line in lines:
if self._importHeaders.GetSelectedState()==1 and i==0:
self._helper.debug("Ignore first line..")
else:
# now parse the rest
splitted = line.split()
x = float(splitted[0])
y = float(splitted[1])
z = float(splitted[2])
if self._importNifti.GetSelectedState()==1:
x = x*(-1)
y = y*(-1)
#self._helper.debug("Found point: "+str(x)+","+str(y)+","+str(z))
id = points.InsertNextPoint(x,y,z)
#self._helper.debug(id)
if lastId:
curLine = slicer.vtkLine()
curLine.GetPointIds().SetId(0,lastId)
curLine.GetPointIds().SetId(1,id)
conn.InsertNextCell(curLine)
#conn.InsertCellPoint(id)
lastId = id
i = i+1
f.close()
result = slicer.vtkPolyData()
result.SetPoints(points)
result.SetLines(conn)
result.Update()
self._helper.debug(result)
outModel.SetAndObservePolyData(result)
outModel.SetModifiedSinceRead(1)
displayNode = outModel.GetModelDisplayNode()
if not displayNode:
displayNode = slicer.vtkMRMLModelDisplayNode()
displayNode.SetPolyData(outModel.GetPolyData())
displayNode.SetColor(0.8, 0, 0)
displayNode.SetVisibility(1)
displayNode.SetOpacity(1.0)
self.GetLogic().GetMRMLScene().AddNode(displayNode)
outModel.SetAndObserveDisplayNodeID(displayNode.GetID())
def Import(self):
outModel = self._importModelSelector.GetSelected()
outputFileName = self._loadButton.GetFileName()
if outModel and outputFileName:
self._helper.debug("Start import..")
points = slicer.vtkPoints()
conn = slicer.vtkCellArray()
polyData = slicer.vtkPolyData()
f = open(outputFileName)
lines = f.readlines()
i = 0
lastId = None
for line in lines:
if self._importHeaders.GetSelectedState() == 1 and i == 0:
self._helper.debug("Ignore first line..")
else:
# now parse the rest
splitted = line.split()
x = float(splitted[0])
y = float(splitted[1])
z = float(splitted[2])
if self._importNifti.GetSelectedState() == 1:
x = x * (-1)
y = y * (-1)
#self._helper.debug("Found point: "+str(x)+","+str(y)+","+str(z))
id = points.InsertNextPoint(x, y, z)
#self._helper.debug(id)
if lastId:
curLine = slicer.vtkLine()
curLine.GetPointIds().SetId(0, lastId)
curLine.GetPointIds().SetId(1, id)
conn.InsertNextCell(curLine)
#conn.InsertCellPoint(id)
lastId = id
i = i + 1
f.close()
result = slicer.vtkPolyData()
result.SetPoints(points)
result.SetLines(conn)
result.Update()
self._helper.debug(result)
outModel.SetAndObservePolyData(result)
outModel.SetModifiedSinceRead(1)
displayNode = outModel.GetModelDisplayNode()
if not displayNode:
displayNode = slicer.vtkMRMLModelDisplayNode()
displayNode.SetPolyData(outModel.GetPolyData())
displayNode.SetColor(0.8, 0, 0)
displayNode.SetVisibility(1)
displayNode.SetOpacity(1.0)
self.GetLogic().GetMRMLScene().AddNode(displayNode)
outModel.SetAndObserveDisplayNodeID(displayNode.GetID())
def Execute(dwi_node, seeds_node, mask_node, ff_node, \
record_fa = False, record_state = False, record_cov = False, \
model="two-tensor", FA_min=.15, GA_min=.10,
seeds=1, labels=[1],
Qm=.0030, Ql=100, Rs=.015, theta_max=45):
for i in xrange(10) : print ''
is_2t = (model == "two-tensor")
print 'HACK hardcode 2T'; is_2t = True
follow = iff(is_2t, follow2t, follow1t)
state_dim = iff(is_2t, 10, 5) # dimension of state space
theta_min = 5 # angle which triggers branch
param = dict({'FA_min': FA_min, # fractional anisotropy stopping threshold
'GA_min': GA_min, # generalized anisotropy stopping threshold
'dt': .2, # forward Euler step size (path integration)
'max_len': 250, # stop if fiber gets this long
'min_radius': .87, # stop if fiber curves this much
'seeds' : seeds, # number of seeds in each voxel
'theta_min': np.cos(theta_min * np.pi/180), # angle which triggers branch
'theta_max': np.cos(theta_max * np.pi/180), # angle which triggers branch
'min_radius': .87, # stop if fiber curves this much
'record_fa' : record_fa,
'record_st' : record_state,
'record_co' : record_cov,
# Kalman filter parameters
'Qm': Qm, # injected angular noise
'Ql': Ql, # injected eigenvalue noise
'Rs': Rs, # dependent on latent noise in your data
'P0': 0.01 * np.eye(state_dim)}) # initial covariance
from Slicer import slicer
# foo = slicer.vtkFloatArray()
# foo.SetNumberOfComponents(1)
# foo.SetName('foo')
# foo.InsertNextValue(234) # Success
# foo.InsertNextValue(23.4) # Success
# foo.InsertNextValue(255 * np.random.rand()) # Success
# foo.InsertNextValue(np.empty(1,dtype='float32')) # FAIL
# foo.InsertNextValue(np.empty(1,dtype='float64')) # FAIL
# asdf
scene = slicer.MRMLScene
dwi_node = scene.GetNodeByID(dwi_node)
seeds_node = scene.GetNodeByID(seeds_node)
mask_node = scene.GetNodeByID(mask_node)
ff_node = scene.GetNodeByID(ff_node)
# ensure normalized signal
bb = dwi_node.GetBValues().ToArray()
if np.any(bb.sum(1) == 0):
import Slicer
Slicer.tk.eval('tk_messageBox -message "Use the \'Normalize Signal\' module to prepare the DWI data"')
return
b = bb.mean()
S = dwi_node.GetImageData().ToArray()
u = dwi_node.GetDiffusionGradients().ToArray()
i2r = vtk2mat(dwi_node.GetIJKToRASMatrix, slicer)
r2i = vtk2mat(dwi_node.GetRASToIJKMatrix, slicer)
mf = vtk2mat(dwi_node.GetMeasurementFrameMatrix, slicer)
voxel = np.mat(dwi_node.GetSpacing()).reshape(3,1)
voxel = voxel[::-1] # HACK Numpy has [z y x]
# generalized loading...
R = r2i[0:3,0:3] / voxel.T # normalize each column
M = mf[0:3,0:3]
# transform gradients
u = dwi_node.GetDiffusionGradients().ToArray()
u = u * (np.linalg.inv(R) * M).T
u = u / np.sqrt(np.power(u,2).sum(1))
u = np.vstack((u,-u)) # duplicate signal
param['voxel'] = voxel
mask = mask_node.GetImageData().ToArray().astype('uint16')
# pull all seeds
seeds_ = seeds_node.GetImageData().ToArray()
seeds = np.zeros(seeds_.shape, dtype='bool')
for lbl in labels:
seeds |= (seeds_ == lbl)
seeds = zip(*seeds.nonzero())
# ensure seeds
if len(seeds) == 0:
import Slicer
Slicer.tk.eval('tk_messageBox -message "No seeds found for this label"')
return
# double check branching
if 0 < theta_max and theta_max < 5:
import Slicer
Slicer.tk.eval('tk_messageBox -message "Nonzero branching angle must be greater than 5 degrees"')
return
is_branching = is_2t and param['theta_max'] < 1
# tractography...
ff1 = init(S, seeds, u, b, param, is_2t)
ff2,ff_fa,ff_st,ff_co = [],[],[],[]
t1 = time.time()
for i in xrange(0,len(ff1)):
print '[%3.0f%%] (%7d - %7d)' % (100.0*i/len(ff1), i, len(ff1))
ff1[i],next,extra = follow(S,u,b,mask,ff1[i],param,is_branching)
ff2.extend(next)
# store extras
if record_fa: ff_fa.append(extra[0])
if record_state: ff_st.append(extra[1])
if record_cov: ff_co.append(extra[2])
t2 = time.time()
print 'Time: ', t2 - t1, 'sec'
if is_branching:
for i in xrange(0,len(ff2)):
print '[%3.0f%%] (%7d - %7d)' % (100.0*i/len(ff2), i, len(ff2))
f,_ = follow(S,u,b,mask,ff2[i],param,False)
ff1.append(f)
print 'Time: ', time.time() - t2, 'sec'
# build polydata
ss_x = slicer.vtkPoints()
lines = slicer.vtkCellArray()
if record_fa: ss_fa = slicer.vtkFloatArray(); ss_fa.SetNumberOfComponents(1); ss_fa.SetName('FA');
if record_state: ss_st = slicer.vtkFloatArray(); ss_st.SetNumberOfComponents(state_dim); ss_st.SetName('state');
if record_cov: ss_co = slicer.vtkFloatArray(); ss_co.SetNumberOfComponents(state_dim**2); ss_co.SetName('covariance');
cell_id = 0
for i in xrange(0,len(ff1)):
f = ff1[i]
lines.InsertNextCell(len(f))
if record_fa: f_fa = ff_fa[i]
if record_state: f_st = ff_st[i]
if record_cov: f_co = ff_co[i]
for j in xrange(0,len(f)):
lines.InsertCellPoint(cell_id)
cell_id += 1
x = f[j]
x = x[::-1] # HACK
x_ = np.array(transform(i2r, x)).ravel() # HACK
ss_x.InsertNextPoint(x_[0],x_[1],x_[2])
if record_fa : ss_fa.InsertNextValue(255 * f_fa[j]) # FIXME numpy type
if record_state : ss_st.InsertNextValue(f_fa[j]) # FIXME tuples?
if record_cov : ss_co.InsertNextValue(f_fa[j]) # FIXME tuples?
# setup output fibers
dnode = ff_node.GetDisplayNode()
if not dnode:
dnode = slicer.vtkMRMLModelDisplayNode()
ff_node.GetScene().AddNodeNoNotify(dnode)
ff_node.SetAndObserveDisplayNodeID(dnode.GetID())
pd = ff_node.GetPolyData()
if not pd:
pd = slicer.vtkPolyData() # create if necessary
ff_node.SetAndObservePolyData(pd)
pd.SetPoints(ss_x)
if record_fa : pd.GetPointData().SetScalars(ss_fa)
pd.SetLines(lines)
pd.Update()
ff_node.Modified()
asdf # HACK flush stdio
