def computeFemoralLandMarkMatrix(txtPath: str):
'''
计算将solidWorks中的假体平移和旋转到原点附近
'''
pSourcePoints = vtk.vtkPoints()
pSourcePoints.InsertPoint(0, -73.292, 1.468, -186.725)
pSourcePoints.InsertPoint(1, -73.6702, 0.964468, -171.738)
pSourcePoints.InsertPoint(2, -73.292, 1.468, -156.725)
# pSourcePoints.InsertPoint(3, 57.6515, 29.5704 , -171.2451)
# pSourcePoints.InsertPoint(4, 115.8690, 3.24210 , -160.804)
pTargetPoints = vtk.vtkPoints()
pTargetPoints.InsertPoint(0, -73.292, 1.468, -186.725)
pTargetPoints.InsertPoint(1, -73.292, 1.468, -171.725)
pTargetPoints.InsertPoint(2, -73.292, 1.468, -156.725) # -y 横向的 后端切平面的法线
# pTargetPoints.InsertPoint(3, -48.651500, 21.57049, -208.7548)
# pTargetPoints.InsertPoint(4, -106.8690, -4.7579, -219.1959) # -z 轴向的 远端切平面的法线
landmarkTransform = vtk.vtkLandmarkTransform()
landmarkTransform.SetSourceLandmarks(pSourcePoints)
landmarkTransform.SetTargetLandmarks(pTargetPoints)
landmarkTransform.SetModeToRigidBody()
landmarkTransform.Update()
matrix = landmarkTransform.GetMatrix()
nparray = arrayFromVTKMatrix(matrix)
for i in range(4):
for j in range(4):
print("{:10.2f}".format(matrix.GetElement(i, j)), end=", ")
print("")
np.set_printoptions(precision=3)
np.savetxt(txtPath, nparray, fmt='%1.3f')
def __init__(self, module_manager):
ModuleBase.__init__(self, module_manager)
self._input_points = [None, None]
self._source_landmarks = None
self._target_landmarks = None
self._config.mode = 'Rigid'
configList = [('Transformation mode:', 'mode', 'base:str', 'choice',
'Rigid: rotation + translation;\n'
'Similarity: rigid + isotropic scaling\n'
'Affine: rigid + scaling + shear',
('Rigid', 'Similarity', 'Affine'))]
self._landmark_transform = vtk.vtkLandmarkTransform()
ScriptedConfigModuleMixin.__init__(
self, configList, {
'Module (self)': self,
'vtkLandmarkTransform': self._landmark_transform
})
self.sync_module_logic_with_config()
def getRigidTransform(fix, mov): # In real resolution
LandmarkTransform = vtk.vtkLandmarkTransform()
LandmarkTransform.SetModeToRigidBody()
n = fix.shape[0]
fix_point = vtk.vtkPoints()
fix_point.SetNumberOfPoints(n)
mov_point = vtk.vtkPoints()
mov_point.SetNumberOfPoints(n)
for i in range(n):
fix_point.SetPoint(i, fix[i, 0], fix[i, 1], fix[i, 2])
mov_point.SetPoint(i, mov[i, 0], mov[i, 1], mov[i, 2])
LandmarkTransform.SetSourceLandmarks(mov_point)
LandmarkTransform.SetTargetLandmarks(fix_point)
LandmarkTransform.Update()
matrix = LandmarkTransform.GetMatrix()
T = ml.zeros([4, 4], dtype = npy.float32)
for i in range(4):
for j in range(4):
T[i, j] = matrix.GetElement(j, i)
p1 = mov[0, :].tolist()
p2 = [0.0, 0, 0]
LandmarkTransform.InternalTransformPoint(p1, p2)
return T, npy.array(p2)
def computeTibiaTrayLandMarkMatrix(txtPath: str):
'''
计算将solidWorks中的假体平移和旋转到原点附近
'''
pSourcePoints = vtk.vtkPoints()
pSourcePoints.InsertPoint(0, 0, 0, 0)
pSourcePoints.InsertPoint(1, 0.5, 0, 0)
pSourcePoints.InsertPoint(2, 1.0, 0, 0)
pSourcePoints.InsertPoint(3, 0, 0.5, 0)
pSourcePoints.InsertPoint(4, 0, 1.0, 0)
pTargetPoints = vtk.vtkPoints()
pTargetPoints.InsertPoint(0, 0, 0, 0)
pTargetPoints.InsertPoint(1, -0.5, 0, 0)
pTargetPoints.InsertPoint(2, -1.0, 0, 0)
pTargetPoints.InsertPoint(3, 0, 0.5, 0)
pTargetPoints.InsertPoint(4, 0, 1.0, 0)
landmarkTransform = vtk.vtkLandmarkTransform()
landmarkTransform.SetSourceLandmarks(pSourcePoints)
landmarkTransform.SetTargetLandmarks(pTargetPoints)
landmarkTransform.SetModeToRigidBody()
landmarkTransform.Update()
matrix = landmarkTransform.GetMatrix()
nparray = arrayFromVTKMatrix(matrix)
for i in range(4):
for j in range(4):
print("{:10.2f}".format(matrix.GetElement(i, j)), end=", ")
print("")
np.set_printoptions(precision=3)
np.savetxt(txtPath, nparray, fmt='%1.3f')
def getRigidTransform(fix, mov): # In real resolution
LandmarkTransform = vtk.vtkLandmarkTransform()
LandmarkTransform.SetModeToRigidBody()
n = fix.shape[0]
fix_point = vtk.vtkPoints()
fix_point.SetNumberOfPoints(n)
mov_point = vtk.vtkPoints()
mov_point.SetNumberOfPoints(n)
for i in range(n):
fix_point.SetPoint(i, fix[i, 0], fix[i, 1], fix[i, 2])
mov_point.SetPoint(i, mov[i, 0], mov[i, 1], mov[i, 2])
LandmarkTransform.SetSourceLandmarks(mov_point)
LandmarkTransform.SetTargetLandmarks(fix_point)
LandmarkTransform.Update()
matrix = LandmarkTransform.GetMatrix()
T = ml.zeros([4, 4], dtype=npy.float32)
for i in range(4):
for j in range(4):
T[i, j] = matrix.GetElement(j, i)
p1 = mov[0, :].tolist()
p2 = [0.0, 0, 0]
LandmarkTransform.InternalTransformPoint(p1, p2)
return T, npy.array(p2)
def onLandmarkMoved_NOT(self,state):
"""Perform the linear transform using the vtkLandmarkTransform class"""
if state.transformed.GetTransformNodeID() != state.linearTransform.GetID():
state.transformed.SetAndObserveTransformNodeID(state.linearTransform.GetID())
self.linearMode = "Rigid"
# try to use user selection, but fall back if not enough points are available
landmarkTransform = vtk.vtkLandmarkTransform()
if self.linearMode == 'Rigid':
landmarkTransform.SetModeToRigidBody()
if self.linearMode == 'Similarity':
landmarkTransform.SetModeToSimilarity()
if self.linearMode == 'Affine':
landmarkTransform.SetModeToAffine()
if state.fixedFiducials.GetNumberOfFiducials() < 3:
landmarkTransform.SetModeToRigidBody()
points = {}
point = [0,]*3
for volumeNode in (state.fixed,state.moving):
points[volumeNode] = vtk.vtkPoints()
indices = range(state.fixedFiducials.GetNumberOfFiducials())
fiducialLists = (state.fixedFiducials,state.movingFiducials)
volumeNodes = (state.fixed,state.moving)
for fiducials,volumeNode in zip(fiducialLists,volumeNodes):
for index in indices:
fiducials.GetNthFiducialPosition(index,point)
points[volumeNode].InsertNextPoint(point)
landmarkTransform.SetSourceLandmarks(points[state.moving])
landmarkTransform.SetTargetLandmarks(points[state.fixed])
landmarkTransform.Update()
t = state.linearTransform
t.SetAndObserveMatrixTransformToParent(landmarkTransform.GetMatrix())
def onLandmarkMoved(self,state):
"""Perform the linear transform using the vtkLandmarkTransform class"""
if state.transformed:
if state.transformed.GetTransformNodeID() != state.transform.GetID():
state.transformed.SetAndObserveTransformNodeID(state.transform.GetID())
if not state.fixedFiducials or not state.movingFiducials:
return
# try to use user selection, but fall back if not enough points are available
landmarkTransform = vtk.vtkLandmarkTransform()
if self.linearMode == 'Rigid':
landmarkTransform.SetModeToRigidBody()
if self.linearMode == 'Similarity':
landmarkTransform.SetModeToSimilarity()
if self.linearMode == 'Affine':
landmarkTransform.SetModeToAffine()
if state.fixedFiducials.GetNumberOfFiducials() < 3:
landmarkTransform.SetModeToRigidBody()
volumeNodes = (state.fixed, state.moving)
fiducialNodes = (state.fixedFiducials,state.movingFiducials)
points = state.logic.vtkPointsForVolumes( volumeNodes, fiducialNodes )
landmarkTransform.SetSourceLandmarks(points[state.moving])
landmarkTransform.SetTargetLandmarks(points[state.fixed])
landmarkTransform.Update()
state.transform.SetAndObserveTransformToParent(landmarkTransform)
def onLandmarkMoved(self, state):
"""Perform the linear transform using the vtkLandmarkTransform class"""
if state.transformed:
if state.transformed.GetTransformNodeID() != state.transform.GetID(
):
state.transformed.SetAndObserveTransformNodeID(
state.transform.GetID())
if not state.fixedFiducials or not state.movingFiducials:
return
# try to use user selection, but fall back if not enough points are available
landmarkTransform = vtk.vtkLandmarkTransform()
if self.linearMode == 'Rigid':
landmarkTransform.SetModeToRigidBody()
if self.linearMode == 'Similarity':
landmarkTransform.SetModeToSimilarity()
if self.linearMode == 'Affine':
landmarkTransform.SetModeToAffine()
if state.fixedFiducials.GetNumberOfFiducials() < 3:
landmarkTransform.SetModeToRigidBody()
volumeNodes = (state.fixed, state.moving)
fiducialNodes = (state.fixedFiducials, state.movingFiducials)
points = state.logic.vtkPointsForVolumes(volumeNodes, fiducialNodes)
landmarkTransform.SetSourceLandmarks(points[state.moving])
landmarkTransform.SetTargetLandmarks(points[state.fixed])
landmarkTransform.Update()
state.transform.SetAndObserveTransformToParent(landmarkTransform)
def performLandmarkRegistion(self, fromFiducialsNode, toFiducialsNode, outputTransformNode):
fromPoints = vtk.vtkPoints()
toPoints = vtk.vtkPoints()
nFrom = fromFiducialsNode.GetNumberOfFiducials()
nTo = toFiducialsNode.GetNumberOfFiducials()
if nFrom != nTo:
logging.error('Number of fiducials in lists are not equal.')
return
for i in range(nFrom):
p = [0, 0, 0]
fromFiducialsNode.GetNthFiducialPosition(i, p)
fromPoints.InsertNextPoint( p )
toFiducialsNode.GetNthFiducialPosition(i, p)
toPoints.InsertNextPoint( p )
lt = vtk.vtkLandmarkTransform()
lt.SetSourceLandmarks(fromPoints)
lt.SetTargetLandmarks(toPoints)
lt.SetModeToRigidBody()
lt.Update()
m = vtk.vtkMatrix4x4()
lt.GetMatrix(m)
#Check for stability of registration
det = m.Determinant()
if det < 1e-8:
logging.error('Unstable registration. Check input for collinear points.')
return
outputTransformNode.SetMatrixTransformToParent(m)
def onLandmarkMoved_NOT(self,state):
"""Perform the linear transform using the vtkLandmarkTransform class"""
if state.transformed.GetTransformNodeID() != state.linearTransform.GetID():
state.transformed.SetAndObserveTransformNodeID(state.linearTransform.GetID())
self.linearMode = "Rigid"
# try to use user selection, but fall back if not enough points are available
landmarkTransform = vtk.vtkLandmarkTransform()
if self.linearMode == 'Rigid':
landmarkTransform.SetModeToRigidBody()
if self.linearMode == 'Similarity':
landmarkTransform.SetModeToSimilarity()
if self.linearMode == 'Affine':
landmarkTransform.SetModeToAffine()
if state.fixedFiducials.GetNumberOfFiducials() < 3:
landmarkTransform.SetModeToRigidBody()
points = {}
point = [0,]*3
for volumeNode in (state.fixed,state.moving):
points[volumeNode] = vtk.vtkPoints()
indices = range(state.fixedFiducials.GetNumberOfFiducials())
fiducialLists = (state.fixedFiducials,state.movingFiducials)
volumeNodes = (state.fixed,state.moving)
for fiducials,volumeNode in zip(fiducialLists,volumeNodes):
for index in indices:
fiducials.GetNthFiducialPosition(index,point)
points[volumeNode].InsertNextPoint(point)
landmarkTransform.SetSourceLandmarks(points[state.moving])
landmarkTransform.SetTargetLandmarks(points[state.fixed])
landmarkTransform.Update()
t = state.linearTransform
t.SetAndObserveMatrixTransformToParent(landmarkTransform.GetMatrix())
def LandmarkSimilitudRegistration(fix, mov):
""" landmarks registration from two vtkPoints """
transform = vtk.vtkLandmarkTransform()
transform.SetSourceLandmarks(mov)
transform.SetTargetLandmarks(fix)
transform.SetModeToSimilarity()
transform.Update()
return transform
def onCalculateButtonClicked(self):
self.landmarkTransform = vtk.vtkLandmarkTransform()
self.landmarkTransform.SetSourceLandmarks(self.collectedPoints)
self.landmarkTransform.SetTargetLandmarks(self.points)
self.landmarkTransform.SetModeToRigidBody()
self.landmarkTransform.Update()
self.outputMatrix = vtk.vtkMatrix4x4()
self.landmarkTransform.GetMatrix(self.outputMatrix)
self.transformTable.setItem(
0, 0, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(0, 0))))
self.transformTable.setItem(
0, 1, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(0, 1))))
self.transformTable.setItem(
0, 2, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(0, 2))))
self.transformTable.setItem(
0, 3, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(0, 3))))
self.transformTable.setItem(
1, 0, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(1, 0))))
self.transformTable.setItem(
1, 1, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(1, 1))))
self.transformTable.setItem(
1, 2, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(1, 2))))
self.transformTable.setItem(
1, 3, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(1, 3))))
self.transformTable.setItem(
2, 0, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(2, 0))))
self.transformTable.setItem(
2, 1, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(2, 1))))
self.transformTable.setItem(
2, 2, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(2, 2))))
self.transformTable.setItem(
2, 3, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(2, 3))))
self.transformTable.setItem(
3, 0, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(3, 0))))
self.transformTable.setItem(
3, 1, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(3, 1))))
self.transformTable.setItem(
3, 2, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(3, 2))))
self.transformTable.setItem(
3, 3, qt.QTableWidgetItem(str(self.outputMatrix.GetElement(3, 3))))
self.transformTable.resizeColumnToContents(0)
self.transformTable.resizeColumnToContents(1)
self.transformTable.resizeColumnToContents(2)
self.transformTable.resizeColumnToContents(3)
self.calNode = slicer.mrmlScene.AddNewNodeByClass(
'vtkMRMLLinearTransformNode', 'JigSensorToJig')
self.calNode.SetMatrixTransformToParent(self.outputMatrix)
self.collectionNode.SetAndObserveTransformNodeID(self.calNode.GetID())
self.array = np.ones(4)
self.transformedArray = np.array(
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
np.float64())
for i in range(0, 6):
self.collectionNode.GetMarkupPointWorld(i, 0, self.array)
self.transformedArray[i] = self.array[0:3]
self.error = np.linalg.norm(self.jigArray - self.transformedArray)
self.errorString.text = "RMSE: " + str(self.error)
def MRIXRayRegistration(self, mriLMReader, wrlLMReader, mriReader):
Transrigid = vtk.vtkLandmarkTransform()
Transrigid.SetSourceLandmarks(mriLMReader.points)
Transrigid.SetTargetLandmarks(wrlLMReader.vertebrae_points)
Transrigid.SetModeToRigidBody()
Transrigid.Update()
mriReader.actor.SetUserTransform(Transrigid)
mriLMReader.actor.SetUserTransform(Transrigid)
print("-----Performance Metrics of MRI to X-Ray using Rigid Registration-----")
self.getMetrics(mriLMReader, wrlLMReader, Transrigid)
def landmark_registration(src, tgt):
'''
src: moving points
tgt: fix points
'''
reg = vtk.vtkLandmarkTransform()
reg.SetSourceLandmarks(src.GetPoints())
reg.SetTargetLandmarks(tgt.GetPoints())
reg.SetModeToRigidBody()
reg.Update()
return reg.GetMatrix()
def vtk_ellipsoid_topomesh(ellipsoid_radius=50.0, ellipsoid_scales=[1,1,1], ellipsoid_axes=np.diag(np.ones(3)), ellipsoid_center=np.zeros(3)):
"""
"""
import vtk
from openalea.cellcomplex.property_topomesh.utils.image_tools import vtk_polydata_to_triangular_mesh
ico = vtk.vtkPlatonicSolidSource()
ico.SetSolidTypeToIcosahedron()
ico.Update()
subdivide = vtk.vtkLoopSubdivisionFilter()
subdivide.SetNumberOfSubdivisions(3)
subdivide.SetInputConnection(ico.GetOutputPort())
subdivide.Update()
scale_transform = vtk.vtkTransform()
scale_factor = ellipsoid_radius/(np.sqrt(2)/2.)
scale_transform.Scale(scale_factor,scale_factor,scale_factor)
ellipsoid_sphere = vtk.vtkTransformPolyDataFilter()
ellipsoid_sphere.SetInput(subdivide.GetOutput())
ellipsoid_sphere.SetTransform(scale_transform)
ellipsoid_sphere.Update()
ellipsoid_transform = vtk.vtkTransform()
axes_transform = vtk.vtkLandmarkTransform()
source_points = vtk.vtkPoints()
source_points.InsertNextPoint([1,0,0])
source_points.InsertNextPoint([0,1,0])
source_points.InsertNextPoint([0,0,1])
target_points = vtk.vtkPoints()
target_points.InsertNextPoint(ellipsoid_axes[0])
target_points.InsertNextPoint(ellipsoid_axes[1])
target_points.InsertNextPoint(ellipsoid_axes[2])
axes_transform.SetSourceLandmarks(source_points)
axes_transform.SetTargetLandmarks(target_points)
axes_transform.SetModeToRigidBody()
axes_transform.Update()
ellipsoid_transform.SetMatrix(axes_transform.GetMatrix())
ellipsoid_transform.Scale(ellipsoid_scales[0],ellipsoid_scales[1],ellipsoid_scales[2])
center_transform = vtk.vtkTransform()
center_transform.Translate(ellipsoid_center[0],ellipsoid_center[1],ellipsoid_center[2])
center_transform.Concatenate(ellipsoid_transform)
ellipsoid_ellipsoid = vtk.vtkTransformPolyDataFilter()
ellipsoid_ellipsoid.SetInput(ellipsoid_sphere.GetOutput())
ellipsoid_ellipsoid.SetTransform(center_transform)
ellipsoid_ellipsoid.Update()
ellipsoid_mesh = vtk_polydata_to_triangular_mesh(ellipsoid_ellipsoid.GetOutput())
topomesh = triangle_topomesh(ellipsoid_mesh.triangles.values(),ellipsoid_mesh.points)
return topomesh
def ICPSimilitudRegistration(fix, mov, fix_ldm=None, mov_ldm=None, do_rigid=False):
"""
IterativeClosestPoint registration between two vtkPolyData
return the vtkTransform
can be initialized using landmarks
(then return a composed vtkTransform instead of a vtkIterativeClosestPointTransform)
"""
transform = vtk.vtkIterativeClosestPointTransform()
if do_rigid:
transform.GetLandmarkTransform().SetModeToRigidBody()
else:
transform.GetLandmarkTransform().SetModeToSimilarity()
transform.SetTarget(fix)
#transform.SetMaximumNumberOfIterations(10)
#transform.SetMaximumNumberOfLandmarks(100)
# initialize using landmarks
if fix_ldm is not None and mov_ldm is not None:
ldm_transform = vtk.vtkLandmarkTransform()
ldm_transform.SetSourceLandmarks(mov_ldm)
ldm_transform.SetTargetLandmarks(fix_ldm)
if do_rigid:
ldm_transform.SetModeToRigidBody()
else:
ldm_transform.SetModeToSimilarity()
ldm_transform.Update()
warper = vtk.vtkTransformPolyDataFilter()
warper.SetTransform(ldm_transform)
warper.SetInputData(mov)
warper.Update()
# ICP registration
transform.SetSource(warper.GetOutput())
transform.Update()
composed = vtk.vtkTransform()
composed.SetInput(transform)
composed.PreMultiply()
composed.Concatenate(ldm_transform)
return composed
else:
transform.SetStartByMatchingCentroids(True)
# ICP registration
transform.SetSource(mov)
transform.Update()
return transform
def constraint(self, x_current):
# Make sure the optimizer is searching in a reasonable region.
# aim to preserve volume using the determinant of the overall affine transform
affine_part = vtk.vtkLandmarkTransform()
source_landmarks = convert_numpy_array_to_vtk_points(x_current)
target_landmarks = convert_numpy_array_to_vtk_points(self.target_landmarks)
affine_part.SetSourceLandmarks(source_landmarks)
affine_part.SetTargetLandmarks(target_landmarks)
affine_part.SetModeToAffine()
affine_part.Update()
det = affine_part.GetMatrix().Determinant()
penalty = -100 * (1 - det)
return penalty
def BestBoundingBox(axis, target, source, targetLandmarks, sourceLandmarks,
bestDistance, bestPoints):
distance = vtk.vtkHausdorffDistancePointSetFilter()
testTransform = vtk.vtkTransform()
testTransformPD = vtk.vtkTransformPolyDataFilter()
lmTransform = vtk.vtkLandmarkTransform()
lmTransformPD = vtk.vtkTransformPolyDataFilter()
lmTransform.SetModeToSimilarity()
lmTransform.SetTargetLandmarks(targetLandmarks.GetPoints())
sourceCenter = sourceLandmarks.GetCenter()
delta = 90.0
for i in range(0, 4):
angle = delta * i
# Rotate about center
testTransform.Identity()
testTransform.Translate(sourceCenter[0], sourceCenter[1],
sourceCenter[2])
if axis == "X":
testTransform.RotateX(angle)
elif axis == "Y":
testTransform.RotateY(angle)
else:
testTransform.RotateZ(angle)
testTransform.Translate(-sourceCenter[0], -sourceCenter[1],
-sourceCenter[2])
testTransformPD.SetTransform(testTransform)
testTransformPD.SetInputData(sourceLandmarks)
testTransformPD.Update()
lmTransform.SetSourceLandmarks(testTransformPD.GetOutput().GetPoints())
lmTransform.Modified()
lmTransformPD.SetInputData(source)
lmTransformPD.SetTransform(lmTransform)
lmTransformPD.Update()
distance.SetInputData(0, target)
distance.SetInputData(1, lmTransformPD.GetOutput())
distance.Update()
testDistance = distance.GetOutput(0).GetFieldData().GetArray(
"HausdorffDistance").GetComponent(0, 0)
if testDistance < bestDistance:
bestDistance = testDistance
bestPoints.DeepCopy(testTransformPD.GetOutput().GetPoints())
return bestDistance
def computeRegistration(referenceToRas, alphaPoints, betaPoints):
landmarkTransform = vtk.vtkLandmarkTransform()
landmarkTransform.SetSourceLandmarks(alphaPoints)
landmarkTransform.SetTargetLandmarks(betaPoints)
landmarkTransform.SetModeToRigidBody()
landmarkTransform.Update()
alphaToBetaMatrix = vtk.vtkMatrix4x4()
landmarkTransform.GetMatrix(alphaToBetaMatrix)
det = alphaToBetaMatrix.Determinant()
if det < 1e-8:
print 'Unstable registration. Check input for collinear points.'
referenceToRas.SetMatrixTransformToParent(alphaToBetaMatrix)
return alphaToBetaMatrix
def transform_lmk(sourcepoints,targetpoints,surface,similarityon=False):
lmktransform = vtk.vtkLandmarkTransform()
lmktransform.SetSourceLandmarks(sourcepoints)
lmktransform.SetTargetLandmarks(targetpoints)
if similarityon:
lmktransform.SetModeToSimilarity()
else:
lmktransform.SetModeToAffine()
lmktransform.Update()
transformfilter = vtk.vtkTransformPolyDataFilter()
transformfilter.SetInputData(surface)
transformfilter.SetTransform(lmktransform)
transformfilter.Update()
return transformfilter.GetOutput()
def SurfaceXRayRegistration(self, szeLMReader, wrlLMReader, szeReader):
# Rotate surface becsause it is not aligned with landmarks
self.AlignSurfaceLM(szeReader)
# find the rigid registration using correspondences
Transrigid = vtk.vtkLandmarkTransform()
Transrigid.SetSourceLandmarks(szeLMReader.points)
Transrigid.SetTargetLandmarks(wrlLMReader.capteurs_points)
Transrigid.SetModeToRigidBody()
Transrigid.Update()
# Apply transformation to landmarks
self.ApplyTransform(szeLMReader.actor, Transrigid)
print("-----Performance Metrics of Surface Topography to X-Ray using Rigid Registration-----")
self.getMetrics(szeLMReader, wrlLMReader, Transrigid)
# Apply transformation to surface
self.ApplyTransform(szeReader.actorCopy, Transrigid)
self.ApplyTransform(szeReader.actor, Transrigid)
def _updateTransform(self):
"""
Update the landmark transform
"""
if PointsSetsIsEmpty(self.landmarkPointSets):
return
numberOfSets = NumberOfSets(self.landmarkPointSets)
fixedPoints = vtkPoints()
movingPoints = vtkPoints()
fixedPoints.SetNumberOfPoints(numberOfSets)
movingPoints.SetNumberOfPoints(numberOfSets)
pointsetIndex = 0
for index in range(len(self.landmarkPointSets)):
pointset = self.landmarkPointSets[index]
if pointset[0] and pointset[1]:
fixedPoint = pointset[0]
movingPoint = pointset[1]
# Transform the point from the moving landmark with the original transform
transPoint = self.originalTransform.TransformPoint(movingPoint)
fixedPoints.SetPoint(pointsetIndex, fixedPoint)
movingPoints.SetPoint(pointsetIndex, transPoint)
pointsetIndex += 1
landmarkTransform = vtkLandmarkTransform()
if self.landmarkTransformType == 0:
landmarkTransform.SetModeToRigidBody()
elif self.landmarkTransformType == 1:
landmarkTransform.SetModeToSimilarity()
elif self.landmarkTransformType == 2:
landmarkTransform.SetModeToAffine()
landmarkTransform.SetSourceLandmarks(fixedPoints)
landmarkTransform.SetTargetLandmarks(movingPoints)
landmarkTransform.Update()
transform = TransformWithMatrix(landmarkTransform.GetMatrix())
transform.Inverse()
transformation = self.multiWidget.transformations[-1]
assert transformation.transformType == Transformation.TypeLandmark
transformation.transform = transform
self.multiWidget.transformations[-1] = transformation
self._updateLandmarkTransforms()
def _updateTransform(self): """ Update the landmark transform """ if PointsSetsIsEmpty(self.landmarkPointSets): return numberOfSets = NumberOfSets(self.landmarkPointSets) fixedPoints = vtkPoints() movingPoints = vtkPoints() fixedPoints.SetNumberOfPoints(numberOfSets) movingPoints.SetNumberOfPoints(numberOfSets) pointsetIndex = 0 for index in range(len(self.landmarkPointSets)): pointset = self.landmarkPointSets[index] if pointset[0] and pointset[1]: fixedPoint = pointset[0] movingPoint = pointset[1] # Transform the point from the moving landmark with the original transform transPoint = self.originalTransform.TransformPoint(movingPoint) fixedPoints.SetPoint(pointsetIndex, fixedPoint) movingPoints.SetPoint(pointsetIndex, transPoint) pointsetIndex += 1 landmarkTransform = vtkLandmarkTransform() if self.landmarkTransformType == 0: landmarkTransform.SetModeToRigidBody() elif self.landmarkTransformType == 1: landmarkTransform.SetModeToSimilarity() elif self.landmarkTransformType == 2: landmarkTransform.SetModeToAffine() landmarkTransform.SetSourceLandmarks(fixedPoints) landmarkTransform.SetTargetLandmarks(movingPoints) landmarkTransform.Update() transform = TransformWithMatrix(landmarkTransform.GetMatrix()) transform.Inverse() transformation = self.multiWidget.transformations[-1] assert transformation.transformType == Transformation.TypeLandmark transformation.transform = transform self.multiWidget.transformations[-1] = transformation self._updateLandmarkTransforms()
def AlignBoundingBoxes(source, target):
# Use OBBTree to create an oriented bounding box for target and source
sourceOBBTree = vtk.vtkOBBTree()
sourceOBBTree.SetDataSet(source)
sourceOBBTree.SetMaxLevel(1)
sourceOBBTree.BuildLocator()
targetOBBTree = vtk.vtkOBBTree()
targetOBBTree.SetDataSet(target)
targetOBBTree.SetMaxLevel(1)
targetOBBTree.BuildLocator()
sourceLandmarks = vtk.vtkPolyData()
sourceOBBTree.GenerateRepresentation(0, sourceLandmarks)
targetLandmarks = vtk.vtkPolyData()
targetOBBTree.GenerateRepresentation(0, targetLandmarks)
lmTransform = vtk.vtkLandmarkTransform()
lmTransform.SetModeToSimilarity()
lmTransform.SetTargetLandmarks(targetLandmarks.GetPoints())
# lmTransformPD = vtk.vtkTransformPolyDataFilter()
bestDistance = vtk.VTK_DOUBLE_MAX
bestPoints = vtk.vtkPoints()
bestDistance = BestBoundingBox("X", target, source, targetLandmarks,
sourceLandmarks, bestDistance, bestPoints)
bestDistance = BestBoundingBox("Y", target, source, targetLandmarks,
sourceLandmarks, bestDistance, bestPoints)
bestDistance = BestBoundingBox("Z", target, source, targetLandmarks,
sourceLandmarks, bestDistance, bestPoints)
lmTransform.SetSourceLandmarks(bestPoints)
lmTransform.Modified()
transformPD = vtk.vtkTransformPolyDataFilter()
transformPD.SetInputData(source)
transformPD.SetTransform(lmTransform)
transformPD.Update()
source.DeepCopy(transformPD.GetOutput())
return
def landmarkRegistration(self, fromMarkupsNode, toMarkupsNode,
outputTransformNode):
logging.debug('landmarkRegistration')
fromPoints = vtk.vtkPoints()
toPoints = vtk.vtkPoints()
nFromPoints = fromMarkupsNode.GetNumberOfFiducials()
nToPoints = toMarkupsNode.GetNumberOfFiducials()
if nFromPoints != nToPoints:
return 'Number of points in markups nodes are not equal. Error {0:.2f}', 1
if nFromPoints < 3:
return 'Insufficient number of points in markups nodes. Error {0:.2f}', 2
for i in range(nFromPoints):
p = [0, 0, 0]
fromMarkupsNode.GetNthControlPointPositionWorld(i, p)
fromPoints.InsertNextPoint(p)
toMarkupsNode.GetNthControlPointPositionWorld(i, p)
toPoints.InsertNextPoint(p)
lt = vtk.vtkLandmarkTransform()
lt.SetSourceLandmarks(fromPoints)
lt.SetTargetLandmarks(toPoints)
lt.SetModeToSimilarity()
lt.Update()
resultsMatrix = vtk.vtkMatrix4x4()
lt.GetMatrix(resultsMatrix)
det = resultsMatrix.Determinant()
if det < 1e-8:
return 'Unstable registration. Check input for collinear points. Error {0:.2f}', 3
outputTransformNode.SetMatrixTransformToParent(resultsMatrix)
return self.calculateRMSE(nFromPoints, fromPoints, toPoints,
resultsMatrix)
def matrixError(self, pre, post):
pSourcePoints = vtk.vtkPoints()
pTargetPoints = vtk.vtkPoints()
# 求取术前空间到术后空间的转换矩阵
for i in range(5):
pTargetPoints.InsertPoint(i, post[i][0], post[i][1], post[i][2])
pSourcePoints.InsertPoint(i, pre[i][0], pre[i][1], pre[i][2])
landmarkTransform = vtk.vtkLandmarkTransform()
landmarkTransform.SetSourceLandmarks(pSourcePoints)
landmarkTransform.SetTargetLandmarks(pTargetPoints)
landmarkTransform.SetModeToRigidBody()
landmarkTransform.Update()
matrix = landmarkTransform.GetMatrix()
matrix_np = self.arrayFromVTKMatrix(matrix)
temp_five = np.ones([5, 3], dtype=float)
temp_dist = []
for i in range(5):
post_temp = np.array([pre[i][0], pre[i][1], pre[i][2], 1])
post_temp_transform = np.matmul(matrix_np, post_temp)
temp_five[i] = post_temp_transform[0:3]
dist = np.linalg.norm(post[i] - post_temp_transform[0:3])
temp_dist.append(dist)
# print("post ", post)
# print("temp_five ", temp_five)
# print("temp_dist ", temp_dist)
temp_dist = np.array(temp_dist)
# print("max error ", np.max(temp_dist))
# 返回最大的偏差
return np.max(temp_dist), matrix_np
def applyLandmarkTransform(self):
if (self.in2_pipe != None):
in1_pts = self.pickerstyle.getNumberOfPoints("in1_pipeline")
in2_pts = self.pickerstyle.getNumberOfPoints("in2_pipeline")
if (in1_pts == in2_pts and in1_pts >= 3):
lm = vtk.vtkLandmarkTransform()
lm.SetTargetLandmarks(
self.pickerstyle.getPoints("in1_pipeline"))
lm.SetSourceLandmarks(
self.pickerstyle.getPoints("in2_pipeline"))
lm.SetModeToRigidBody()
lm.Update()
mat = lm.GetMatrix()
self.in2_pipe.setRigidBodyTransformConcatenateMatrix(mat)
self.pickerstyle.removePoints("in1_pipeline")
self.pickerstyle.removePoints("in2_pipeline")
self.refreshRenderWindow()
self.updateGUI()
self.statusBar().showMessage(
f"Landmark transform complete based on {in1_pts}", 4000)
else:
self.statusBar().showMessage(
"ERROR: Landmark transform could not be executed", 4000)
def affine_alignment(source_mesh, source_landmarks, target_landmarks):
"""
Applies an affine transformation to the source mesh and landmarks
:param source_mesh: vtkPolyData to be transformed
:param source_landmarks: array of shape [n,3]
:param target_landmarks: array of shape [n,3]
:return: (transformed source_mesh, transformed source_landmarks)
"""
tar = utils.np_to_vtkPoints(target_landmarks)
src = utils.np_to_vtkPoints(source_landmarks)
src_poly = vtk.vtkPolyData()
src_poly.SetPoints(src)
affine = vtk.vtkLandmarkTransform()
affine.SetSourceLandmarks(src)
affine.SetTargetLandmarks(tar)
affine.SetModeToAffine()
affine.Update()
transform_mesh = vtk.vtkTransformPolyDataFilter()
transform_mesh.SetTransform(affine)
transform_mesh.SetInputData(source_mesh)
transform_mesh.Update()
transformed_mesh = transform_mesh.GetOutput()
transform_landmarks = vtk.vtkTransformPolyDataFilter()
transform_landmarks.SetTransform(affine)
transform_landmarks.SetInputData(src_poly)
transform_landmarks.Update()
transformed_landmarks = utils.vtkPoints_to_np(
transform_landmarks.GetOutput().GetPoints())
return (transformed_mesh, transformed_landmarks)
def __init__(self, master=None):
if master is None:
master = Toplevel()
master.wm_title("Registration")
Frame.__init__(self, master)
self.pack(fill='both', expand='true')
else:
Frame.__init__(self, master)
# the lists of landmarks
self._SourceLandmarks = []
self._TargetLandmarks = []
# the index of the current landmark
self._CurrentLandmark = 0
# the transformation that matches the landmarks
self._SourcePoints = vtk.vtkPoints()
self._TargetPoints = vtk.vtkPoints()
self._Transform = vtk.vtkLandmarkTransform()
# self._Transform.SetModeToRigidBody()
self._Transform.SetSourceLandmarks(self._SourcePoints)
self._Transform.SetTargetLandmarks(self._TargetPoints)
# the FiducialMarkerFactory draws the annotations on the image
self._FiducialMarkerFactory = None
# the OrthoPlanesFactory acts as the cursor for Source points
self._OrthoPlanesFactory = None
# the TrackedPointer acts as the cursor for Target points
self._TrackedPointer = None
# a list of 2D panes: whenever a point is chosen, these will
# be adjusted to ensure that the point is visible
self._Panes = []
# build the user interface
mframe = Frame(self)
lframe = Frame(mframe)
self._Scrollbar = Scrollbar(lframe, relief='sunken', bd=2)
self._Listbox = Listbox(
lframe,
yscrollcommand=self._Scrollbar.set,
# selectmode='multiple',
exportselection='false',
font='courier',
width=len(toanatomic(0, 0, 0)) + 6)
self._Listbox.bind("<ButtonRelease-1>", self._Select)
self._Listbox.bind("<KeyRelease>", self._SelectKey)
# self._Listbox.bind("<KeyRelease-KP_Delete>",
# lambda e,f=self._Delete: f())
self._Listbox.bind("<KeyRelease-Delete>",
lambda e, f=self._Delete: f())
# self._Listbox.bind("<KeyRelease-KP_Enter>",
# lambda e,f=self._Add: f())
self._Listbox.bind("<KeyRelease-Return>", lambda e, f=self._Add: f())
self._Scrollbar.config(command=self._Listbox.yview)
self._Listbox.pack(side='left', fill='both', expand='true')
self._Scrollbar.pack(side='left', fill='y')
lframe.pack(side='left', fill='both', expand='true')
bframe1 = Frame(mframe, bd=1)
bframe = Frame(bframe1, relief='sunken', bd=1)
self._AddB = Button(bframe, text='Add', command=self._Add)
self._NextB = Button(bframe, text='Next', command=self._Next)
self._SetB = Button(bframe, text='Set', command=self._Set)
self._PrevB = Button(bframe, text='Prev', command=self._Prev)
self._DeleteB = Button(bframe, text='Delete', command=self._Delete)
self._AddB.pack(side='top', fill='both', expand='true')
self._NextB.pack(side='top', fill='both', expand='true')
self._SetB.pack(side='top', fill='both', expand='true')
self._PrevB.pack(side='top', fill='both', expand='true')
self._DeleteB.pack(side='top', fill='both', expand='true')
bframe.pack(side='left', fill='both', expand='true')
bframe1.pack(side='left', fill='both', expand='true')
mframe.pack(side='top', fill='both', expand='true')
self._StdDevLabel = Label(
self, text='Standard Deviation: --- mm (0 Points)')
self._StdDevLabel.pack(side='top', fill='y', expand='true')
def register(self, fixedData, movingData, index = -1, discard = False, delta = 0, fov = 9999999.0,
down_fix = 1, down_mov = 1, occ = 9999999.0, op = False, useMask = False, isTime = False, MaxRate = 0.2,
aug = False, distance_fix = 0.3, distance_mov = 0.1, w_wrong = 1.5, truth_mov = None):
time1 = time.time()
if index == -1:
index = self.gui.getDataIndex({'Contour': 0, 'Centerline': 1}, 'Select the object')
if index is None:
return None, None, None
if index == 0:
fixed_points = fixedData.getPointSet('Contour').copy()
moving_points = movingData.getPointSet('Contour').copy()
else:
fixed_points = fixedData.getPointSet('Centerline').copy()
moving_points = movingData.getPointSet('Centerline').copy()
if truth_mov is None:
truth_mov = moving_points.copy()
fixed_bif = db.getBifurcation(fixed_points)
moving_bif = db.getBifurcation(moving_points)
if useMask:
mask_points = movingData.getPointSet('Mask')
for point in mask_points:
moving_points = npy.delete(moving_points, npy.where((npy.abs(moving_points[:, 2] - point[2]) < 0.0001) & (npy.round(moving_points[:, -1]) == point[3])), axis = 0)
fixed_res = fixedData.getResolution().tolist()
moving_res = movingData.getResolution().tolist()
fixed_points = fixed_points[npy.where(fixed_points[:, 0] >= 0)]
moving_points = moving_points[npy.where(moving_points[:, 0] >= 0)]
# Use the bifurcation as the initial position
if (fixed_bif < 0) or (moving_bif < 0):
fixed_min = 0
# Augmentation of pointset
fixed = fixed_points.copy()
moving = moving_points.copy()
if index == 1 and aug:
fixed = util.augmentCenterline(fixed, 1, 10)
moving = util.augmentCenterline(moving, 1, 10)
fix_dis = util.getAxisSin(fixed, 3 / fixed_res[2]) * distance_fix
mov_dis = util.getAxisSin(moving, 3 / moving_res[2]) * distance_mov
fixed = util.resampleCenterline(fixed, fix_dis / fixed_res[2])
moving = util.resampleCenterline(moving, mov_dis / moving_res[2])
fixed = fixed[npy.cast[npy.int32](npy.abs(fixed[:, 2] - fixed_bif)) % down_fix == 0]
moving = moving[npy.cast[npy.int32](npy.abs(moving[:, 2] - moving_bif)) % down_mov == 0]
fixed[:, :3] *= fixed_res[:3]
moving[:, :3] *= moving_res[:3]
new_trans_points = truth_mov
result_center_points = movingData.getPointSet('Centerline').copy()
new_trans_points = new_trans_points[new_trans_points[:, 3] >= 0]
result_center_points = result_center_points[result_center_points[:, 3] >= 0]
new_trans_points[:, :3] *= moving_res[:3]
result_center_points[:, :3] *= moving_res[:3]
if (fixed_bif >= 0) and (moving_bif >= 0):
fixed[:, 2] -= (fixed_bif * fixed_res[2] - moving_bif * moving_res[2] + delta)
# Prepare for ICP
MaxIterNum = 50
#MaxNum = 600
MaxNum = int(MaxRate * moving.shape[0] + 0.5)
targetPoints = [vtk.vtkPoints(), vtk.vtkPoints(), vtk.vtkPoints()]
targetVertices = [vtk.vtkCellArray(), vtk.vtkCellArray(), vtk.vtkCellArray()]
target = [vtk.vtkPolyData(), vtk.vtkPolyData(), vtk.vtkPolyData()]
Locator = [vtk.vtkCellLocator(), vtk.vtkCellLocator(), vtk.vtkCellLocator()]
for i in range(3):
for x in fixed[npy.round(fixed[:, 3]) == i]:
id = targetPoints[i].InsertNextPoint(x[0], x[1], x[2])
targetVertices[i].InsertNextCell(1)
targetVertices[i].InsertCellPoint(id)
target[i].SetPoints(targetPoints[i])
target[i].SetVerts(targetVertices[i])
Locator[i].SetDataSet(target[i])
Locator[i].SetNumberOfCellsPerBucket(1)
Locator[i].BuildLocator()
step = 1
if moving.shape[0] > MaxNum:
ind = moving[:, 2].argsort()
moving = moving[ind, :]
step = moving.shape[0] / MaxNum
nb_points = moving.shape[0] / step
points1 = vtk.vtkPoints()
points1.SetNumberOfPoints(nb_points)
label = npy.zeros([MaxNum * 2], dtype = npy.int8)
j = 0
for i in range(nb_points):
points1.SetPoint(i, moving[j][0], moving[j][1], moving[j][2])
label[i] = moving[j][3]
j += step
closestp = vtk.vtkPoints()
closestp.SetNumberOfPoints(nb_points)
points2 = vtk.vtkPoints()
points2.SetNumberOfPoints(nb_points)
id1 = id2 = vtk.mutable(0)
dist = vtk.mutable(0.0)
outPoint = [0.0, 0.0, 0.0]
p1 = [0.0, 0.0, 0.0]
p2 = [0.0, 0.0, 0.0]
iternum = 0
a = points1
b = points2
if (op and index == 0) or (not op and index == 1):
w_mat = [[1, w_wrong, w_wrong], [w_wrong, 1, 99999999], [w_wrong, 99999999, 1]]
else:
w_mat = [[1, 1, 1], [1, 1, 1], [1, 1, 1]]
accumulate = vtk.vtkTransform()
accumulate.PostMultiply()
LandmarkTransform = vtk.vtkLandmarkTransform()
LandmarkTransform.SetModeToRigidBody()
while True:
for i in range(nb_points):
min_dist = 99999999
min_outPoint = [0.0, 0.0, 0.0]
for j in range(3):
Locator[j].FindClosestPoint(a.GetPoint(i), outPoint, id1, id2, dist)
dis = npy.sqrt(npy.sum((npy.array(outPoint) - a.GetPoint(i)) ** 2))
if dis * w_mat[label[i]][j] < min_dist:
min_dist = dis * w_mat[label[i]][j]
min_outPoint = copy.deepcopy(outPoint)
closestp.SetPoint(i, min_outPoint)
LandmarkTransform.SetSourceLandmarks(a)
LandmarkTransform.SetTargetLandmarks(closestp)
LandmarkTransform.Update()
accumulate.Concatenate(LandmarkTransform.GetMatrix())
iternum += 1
for i in range(nb_points):
a.GetPoint(i, p1)
LandmarkTransform.InternalTransformPoint(p1, p2)
b.SetPoint(i, p2)
b, a = a, b
if iternum >= MaxIterNum:
break
matrix = accumulate.GetMatrix()
T = ml.mat([matrix.GetElement(0, 3), matrix.GetElement(1, 3), matrix.GetElement(2, 3)]).T
R = ml.mat([[matrix.GetElement(0, 0), matrix.GetElement(0, 1), matrix.GetElement(0, 2)],
[matrix.GetElement(1, 0), matrix.GetElement(1, 1), matrix.GetElement(1, 2)],
[matrix.GetElement(2, 0), matrix.GetElement(2, 1), matrix.GetElement(2, 2)]]).I
result_center_points[:, :3] = util.applyTransformForPoints(result_center_points[:, :3], npy.array([1.0, 1, 1]), npy.array([1.0, 1, 1]), R, T, ml.zeros([3, 1], dtype = npy.float32))
new_trans_points[:, :3] = util.applyTransformForPoints(new_trans_points[:, :3], npy.array([1.0, 1, 1]), npy.array([1.0, 1, 1]), R, T, ml.zeros([3, 1], dtype = npy.float32))
LandmarkTransform = vtk.vtkThinPlateSplineTransform()
LandmarkTransform.SetBasisToR()
iternum = 0
# Non-rigid
while True:
for i in range(nb_points):
min_dist = 99999999
min_outPoint = [0.0, 0.0, 0.0]
for j in range(3):
Locator[j].FindClosestPoint(a.GetPoint(i), outPoint, id1, id2, dist)
dis = npy.sqrt(npy.sum((npy.array(outPoint) - a.GetPoint(i)) ** 2))
if dis * w_mat[label[i]][j] < min_dist:
min_dist = dis * w_mat[label[i]][j]
min_outPoint = copy.deepcopy(outPoint)
closestp.SetPoint(i, min_outPoint)
LandmarkTransform.SetSourceLandmarks(a)
LandmarkTransform.SetTargetLandmarks(closestp)
LandmarkTransform.Update()
'''
for i in range(result_center_points.shape[0]):
LandmarkTransform.InternalTransformPoint([result_center_points[i, 0], result_center_points[i, 1], result_center_points[i, 2]], p2)
result_center_points[i, :3] = p2
'''
for i in range(new_trans_points.shape[0]):
LandmarkTransform.InternalTransformPoint([new_trans_points[i, 0], new_trans_points[i, 1], new_trans_points[i, 2]], p2)
new_trans_points[i, :3] = p2
iternum += 1
if iternum >= 1:
break
for i in range(nb_points):
a.GetPoint(i, p1)
LandmarkTransform.InternalTransformPoint(p1, p2)
b.SetPoint(i, p2)
b, a = a, b
time2 = time.time()
if (fixed_bif >= 0) and (moving_bif >= 0):
new_trans_points[:, 2] += (fixed_bif * fixed_res[2] - moving_bif * moving_res[2] + delta)
result_center_points[:, 2] += (fixed_bif * fixed_res[2] - moving_bif * moving_res[2] + delta)
new_trans_points[:, :3] /= fixed_res[:3]
result_center_points[:, :3] /= fixed_res[:3]
resultImage = movingData.getData().copy()
sa = SurfaceErrorAnalysis(None)
dataset = db.BasicData(npy.array([[[0]]]), fixedData.getInfo(), {'Contour': new_trans_points, 'Centerline': result_center_points})
mean_dis, mean_whole, max_dis, max_whole = sa.analysis(dataset, point_data_fix = fixedData.getPointSet('Contour').copy(), useResult = True)
del dataset
print mean_dis
print mean_whole
if isTime:
return resultImage, {'Contour': new_trans_points, 'Centerline': result_center_points}, [mean_dis, mean_whole], time2 - time1
return resultImage, {'Contour': new_trans_points, 'Centerline': result_center_points}, [mean_dis, mean_whole]
# read source landmarks
SourceLMReader = vtk.vtkPolyDataReader()
SourceLMReader.SetFileName("DefaultLandmarks.vtk");
SourceLMReader.Update()
#print SourceLMReader.GetOutput().GetPoints()
# read target landmarks
TargetLMReader = vtk.vtkPolyDataReader()
TargetLMReader.SetFileName("TargetLandmarks.vtk");
TargetLMReader.Update()
#print TargetLMReader.GetOutput().GetPoints()
# create transformation
LandmarkTransform = vtk.vtkLandmarkTransform()
LandmarkTransform.SetSourceLandmarks(SourceLMReader.GetOutput().GetPoints() )
LandmarkTransform.SetTargetLandmarks(TargetLMReader.GetOutput().GetPoints() )
LandmarkTransform.SetModeToRigidBody()
LandmarkTransform.Update()
print LandmarkTransform.GetMatrix()
# apply transform
transformFilter = vtk.vtkTransformFilter()
#transformFilter.SetInput(vtkCylinder.GetOutput() )
transformFilter.SetInput(trianglefilter.GetOutput() )
transformFilter.SetTransform( LandmarkTransform)
transformFilter.Update()
# write model
modelWriter = vtk.vtkDataSetWriter()
def __init__(self, master=None):
if master is None:
master = Toplevel()
master.wm_title("Registration")
Frame.__init__(self, master)
self.pack(fill='both', expand='true')
else:
Frame.__init__(self, master)
# the lists of landmarks
self._SourceLandmarks = []
self._TargetLandmarks = []
# the index of the current landmark
self._CurrentLandmark = 0
# the transformation that matches the landmarks
self._SourcePoints = vtk.vtkPoints()
self._TargetPoints = vtk.vtkPoints()
self._Transform = vtk.vtkLandmarkTransform()
# self._Transform.SetModeToRigidBody()
self._Transform.SetSourceLandmarks(self._SourcePoints)
self._Transform.SetTargetLandmarks(self._TargetPoints)
# the FiducialMarkerFactory draws the annotations on the image
self._FiducialMarkerFactory = None
# the OrthoPlanesFactory acts as the cursor for Source points
self._OrthoPlanesFactory = None
# the TrackedPointer acts as the cursor for Target points
self._TrackedPointer = None
# a list of 2D panes: whenever a point is chosen, these will
# be adjusted to ensure that the point is visible
self._Panes = []
# build the user interface
mframe = Frame(self)
lframe = Frame(mframe)
self._Scrollbar = Scrollbar(lframe,
relief='sunken',
bd=2)
self._Listbox = Listbox(lframe,
yscrollcommand=self._Scrollbar.set,
# selectmode='multiple',
exportselection='false',
font='courier',
width=len(toanatomic(0, 0, 0)) + 6)
self._Listbox.bind("<ButtonRelease-1>", self._Select)
self._Listbox.bind("<KeyRelease>", self._SelectKey)
# self._Listbox.bind("<KeyRelease-KP_Delete>",
# lambda e,f=self._Delete: f())
self._Listbox.bind("<KeyRelease-Delete>",
lambda e, f=self._Delete: f())
# self._Listbox.bind("<KeyRelease-KP_Enter>",
# lambda e,f=self._Add: f())
self._Listbox.bind("<KeyRelease-Return>",
lambda e, f=self._Add: f())
self._Scrollbar.config(command=self._Listbox.yview)
self._Listbox.pack(side='left', fill='both', expand='true')
self._Scrollbar.pack(side='left', fill='y')
lframe.pack(side='left', fill='both', expand='true')
bframe1 = Frame(mframe, bd=1)
bframe = Frame(bframe1, relief='sunken', bd=1)
self._AddB = Button(bframe, text='Add', command=self._Add)
self._NextB = Button(bframe, text='Next', command=self._Next)
self._SetB = Button(bframe, text='Set', command=self._Set)
self._PrevB = Button(bframe, text='Prev', command=self._Prev)
self._DeleteB = Button(bframe, text='Delete', command=self._Delete)
self._AddB.pack(side='top', fill='both', expand='true')
self._NextB.pack(side='top', fill='both', expand='true')
self._SetB.pack(side='top', fill='both', expand='true')
self._PrevB.pack(side='top', fill='both', expand='true')
self._DeleteB.pack(side='top', fill='both', expand='true')
bframe.pack(side='left', fill='both', expand='true')
bframe1.pack(side='left', fill='both', expand='true')
mframe.pack(side='top', fill='both', expand='true')
self._StdDevLabel = Label(self,
text='Standard Deviation: --- mm (0 Points)')
self._StdDevLabel.pack(side='top', fill='y', expand='true')
def register(self,
fixedData,
movingData,
index=-1,
discard=False,
delta=0,
fov=9999999.0,
down_fix=1,
down_mov=1,
occ=9999999.0,
useMask=False,
isTime=False,
MaxRate=0.2,
aug=False,
distance_fix=0.3,
distance_mov=0.1,
w_wrong=1.5):
time1 = time.time()
if index == -1:
index = self.gui.getDataIndex({
'Contour': 0,
'Centerline': 1
}, 'Select the object')
if index is None:
return None, None, None
if index == 0:
fixed_points = fixedData.getPointSet('Contour').copy()
moving_points = movingData.getPointSet('Contour').copy()
else:
fixed_points = fixedData.getPointSet('Centerline').copy()
moving_points = movingData.getPointSet('Centerline').copy()
fixed_bif = db.getBifurcation(fixed_points)
moving_bif = db.getBifurcation(moving_points)
if useMask:
mask_points = movingData.getPointSet('Mask')
for point in mask_points:
moving_points = npy.delete(
moving_points,
npy.where(
(npy.abs(moving_points[:, 2] - point[2]) < 0.0001)
& (npy.round(moving_points[:, -1]) == point[3])),
axis=0)
fixed_res = fixedData.getResolution().tolist()
moving_res = movingData.getResolution().tolist()
fixed_points = fixed_points[npy.where(fixed_points[:, 0] >= 0)]
moving_points = moving_points[npy.where(moving_points[:, 0] >= 0)]
# Use the bifurcation as the initial position
if (fixed_bif < 0) or (moving_bif < 0):
fixed_min = 0
# Augmentation of pointset
fixed = fixed_points.copy()
moving = moving_points.copy()
if index == 1 and aug:
fixed = util.augmentCenterline(fixed, 1, 10)
moving = util.augmentCenterline(moving, 1, 10)
fix_dis = util.getAxisSin(fixed, 3 / fixed_res[2]) * distance_fix
mov_dis = util.getAxisSin(moving, 3 / moving_res[2]) * distance_mov
fixed = util.resampleCenterline(fixed, fix_dis / fixed_res[2])
moving = util.resampleCenterline(moving, mov_dis / moving_res[2])
fixed = fixed[npy.cast[npy.int32](npy.abs(fixed[:, 2] - fixed_bif)) %
down_fix == 0]
moving = moving[npy.cast[npy.int32](npy.abs(moving[:, 2] -
moving_bif)) %
down_mov == 0]
fixed[:, :3] *= fixed_res[:3]
moving[:, :3] *= moving_res[:3]
if (fixed_bif >= 0) and (moving_bif >= 0):
fixed[:, 2] -= (fixed_bif * fixed_res[2] -
moving_bif * moving_res[2] + delta)
# Prepare for ICP
LandmarkTransform = vtk.vtkLandmarkTransform()
LandmarkTransform.SetModeToRigidBody()
MaxIterNum = 50
#MaxNum = 600
MaxNum = int(MaxRate * moving.shape[0] + 0.5)
targetPoints = [vtk.vtkPoints(), vtk.vtkPoints(), vtk.vtkPoints()]
targetVertices = [
vtk.vtkCellArray(),
vtk.vtkCellArray(),
vtk.vtkCellArray()
]
target = [vtk.vtkPolyData(), vtk.vtkPolyData(), vtk.vtkPolyData()]
Locator = [
vtk.vtkCellLocator(),
vtk.vtkCellLocator(),
vtk.vtkCellLocator()
]
for i in range(3):
for x in fixed[npy.round(fixed[:, 3]) == i]:
id = targetPoints[i].InsertNextPoint(x[0], x[1], x[2])
targetVertices[i].InsertNextCell(1)
targetVertices[i].InsertCellPoint(id)
target[i].SetPoints(targetPoints[i])
target[i].SetVerts(targetVertices[i])
Locator[i].SetDataSet(target[i])
Locator[i].SetNumberOfCellsPerBucket(1)
Locator[i].BuildLocator()
step = 1
if moving.shape[0] > MaxNum:
ind = moving[:, 2].argsort()
moving = moving[ind, :]
step = moving.shape[0] / MaxNum
nb_points = moving.shape[0] / step
accumulate = vtk.vtkTransform()
accumulate.PostMultiply()
points1 = vtk.vtkPoints()
points1.SetNumberOfPoints(nb_points)
label = npy.zeros([MaxNum * 2], dtype=npy.int8)
j = 0
for i in range(nb_points):
points1.SetPoint(i, moving[j][0], moving[j][1], moving[j][2])
label[i] = moving[j][3]
j += step
closestp = vtk.vtkPoints()
closestp.SetNumberOfPoints(nb_points)
points2 = vtk.vtkPoints()
points2.SetNumberOfPoints(nb_points)
id1 = id2 = vtk.mutable(0)
dist = vtk.mutable(0.0)
outPoint = [0.0, 0.0, 0.0]
p1 = [0.0, 0.0, 0.0]
p2 = [0.0, 0.0, 0.0]
iternum = 0
a = points1
b = points2
w_mat = [[1, w_wrong, w_wrong], [w_wrong, 1, 99999999],
[w_wrong, 99999999, 1]]
while True:
for i in range(nb_points):
min_dist = 99999999
min_outPoint = [0.0, 0.0, 0.0]
for j in range(3):
Locator[j].FindClosestPoint(a.GetPoint(i), outPoint, id1,
id2, dist)
dis = npy.sqrt(
npy.sum((npy.array(outPoint) - a.GetPoint(i))**2))
if dis * w_mat[label[i]][j] < min_dist:
min_dist = dis * w_mat[label[i]][j]
min_outPoint = copy.deepcopy(outPoint)
closestp.SetPoint(i, min_outPoint)
LandmarkTransform.SetSourceLandmarks(a)
LandmarkTransform.SetTargetLandmarks(closestp)
LandmarkTransform.Update()
accumulate.Concatenate(LandmarkTransform.GetMatrix())
iternum += 1
if iternum >= MaxIterNum:
break
for i in range(nb_points):
a.GetPoint(i, p1)
LandmarkTransform.InternalTransformPoint(p1, p2)
b.SetPoint(i, p2)
b, a = a, b
time2 = time.time()
# Get the result transformation parameters
matrix = accumulate.GetMatrix()
T = ml.mat([
matrix.GetElement(0, 3),
matrix.GetElement(1, 3),
matrix.GetElement(2, 3)
]).T
R = ml.mat([[
matrix.GetElement(0, 0),
matrix.GetElement(0, 1),
matrix.GetElement(0, 2)
],
[
matrix.GetElement(1, 0),
matrix.GetElement(1, 1),
matrix.GetElement(1, 2)
],
[
matrix.GetElement(2, 0),
matrix.GetElement(2, 1),
matrix.GetElement(2, 2)
]]).I
if (fixed_bif >= 0) and (moving_bif >= 0):
T[2] += (fixed_bif * fixed_res[2] - moving_bif * moving_res[2] +
delta)
# Resample the moving contour
moving_points = movingData.getPointSet('Contour').copy()
moving_center = movingData.getPointSet('Centerline').copy()
new_trans_points, result_center_points = moving_points, moving_center
result_center_points[:, :3] = util.applyTransformForPoints(
result_center_points[:, :3], moving_res, fixed_res, R, T,
ml.zeros([3, 1], dtype=npy.float32))
new_trans_points[:, :3] = util.applyTransformForPoints(
new_trans_points[:, :3], moving_res, fixed_res, R, T,
ml.zeros([3, 1], dtype=npy.float32))
T = -T
T = R * T
transform = sitk.Transform(3, sitk.sitkAffine)
para = R.reshape(1, -1).tolist()[0] + T.T.tolist()[0]
transform.SetParameters(para)
movingImage = movingData.getSimpleITKImage()
fixedImage = fixedData.getSimpleITKImage()
resultImage = sitk.Resample(movingImage, fixedImage, transform,
sitk.sitkLinear, 0, sitk.sitkFloat32)
if isTime:
return sitk.GetArrayFromImage(resultImage), {
'Contour': new_trans_points,
'Centerline': result_center_points
}, para + [0, 0, 0], time2 - time1
return sitk.GetArrayFromImage(resultImage), {
'Contour': new_trans_points,
'Centerline': result_center_points
}, para + [0, 0, 0]
def __init__(self, comedi, config_dict):
"""
@param comedi: Instance of comedi that will be used to update
GUI and views.
@param config_dict: This dict, part of the main module config,
will be kept up to date throughout.
"""
self._comedi = comedi
self._cfg = config_dict
# if we get an empty config dict, configure!
if 'data1_landmarks' not in self._cfg:
self._cfg['data1_landmarks'] = {}
# do the list
cp = comedi._view_frame.pane_controls.window
r1 = comedi._data1_slice_viewer.renderer
self._data1_landmarks = \
LandmarkList(
self._cfg['data1_landmarks'],
cp.data1_landmarks_olv, r1)
if 'data2_landmarks' not in self._cfg:
self._cfg['data2_landmarks'] = {}
r2 = comedi._data2_slice_viewer.renderer
self._data2_landmarks = \
LandmarkList(
self._cfg['data2_landmarks'],
cp.data2_landmarks_olv, r2)
self._setup_ui()
self._bind_events()
# we'll use this to store a binding to the current output
self._output = None
# and this to store a binding to the current confidence
self._confidence = None
# remember, this turns out to be the transform itself
self._landmark = vtk.vtkLandmarkTransform()
# and this guy is going to do the work
self._trfm = vtk.vtkImageReslice()
self._trfm.SetInterpolationModeToLinear()
# setup a progress message:
module_utils.setup_vtk_object_progress(
self._comedi, self._trfm,
'Transforming Data 2')
# distance field will be calculated up to this distance,
# saving you time and money!
if KEY_MAX_DISTANCE not in self._cfg:
self._cfg[KEY_MAX_DISTANCE] = 43
md = self._cfg[KEY_MAX_DISTANCE]
print "sslm starting itk init"
# use itk fast marching to generate confidence field
self._fm = itk.FastMarchingImageFilter.IF3IF3.New()
self._fm.SetStoppingValue(md)
self._fm.SetSpeedConstant(1.0)
# setup a progress message
print "sslm fm progress start"
itk_kit.utils.setup_itk_object_progress(
self, self._fm, 'itkFastMarchingImageFilter',
'Propagating confidence front.', None,
comedi._module_manager)
print "sslm fm progress end"
# and a threshold to clip off the really high values that fast
# marching inserts after its max distance
self._thresh = t = itk.ThresholdImageFilter.IF3.New()
t.SetOutsideValue(md)
# values equal to or greater than this are set to outside value
t.ThresholdAbove(md)
itk_kit.utils.setup_itk_object_progress(
self, self._thresh, 'itkThresholdImageFilter',
'Clipping high values in confidence field.', None,
comedi._module_manager)
t.SetInput(self._fm.GetOutput())
# and a little something to convert it back to VTK world
self._itk2vtk = itk.ImageToVTKImageFilter.IF3.New()
self._itk2vtk.SetInput(t.GetOutput())
print "sslm mm init end"
## delny.Update()
# read source landmarks
SourceLMReader = vtk.vtkPolyDataReader()
SourceLMReader.SetFileName("DefaultLandmarks.vtk")
SourceLMReader.Update()
#print SourceLMReader.GetOutput().GetPoints()
# read target landmarks
TargetLMReader = vtk.vtkPolyDataReader()
TargetLMReader.SetFileName("TargetLandmarks.vtk")
TargetLMReader.Update()
#print TargetLMReader.GetOutput().GetPoints()
# create transformation
LandmarkTransform = vtk.vtkLandmarkTransform()
LandmarkTransform.SetSourceLandmarks(SourceLMReader.GetOutput().GetPoints())
LandmarkTransform.SetTargetLandmarks(TargetLMReader.GetOutput().GetPoints())
LandmarkTransform.SetModeToRigidBody()
LandmarkTransform.Update()
print LandmarkTransform.GetMatrix()
# apply transform
transformFilter = vtk.vtkTransformFilter()
#transformFilter.SetInput(vtkCylinder.GetOutput() )
transformFilter.SetInput(trianglefilter.GetOutput())
transformFilter.SetTransform(LandmarkTransform)
transformFilter.Update()
# write model
modelWriter = vtk.vtkDataSetWriter()
def distanceAndAngleCompute(self, num=7):
pSourcePoints = vtk.vtkPoints()
pTargetPoints = vtk.vtkPoints()
# 求取术后空间到术前空间的转换矩阵
for i in range(num):
pTargetPoints.InsertPoint(i, self.preoperative[i][0],
self.preoperative[i][1],
self.preoperative[i][2])
pSourcePoints.InsertPoint(i, self.postoperative[i][0],
self.postoperative[i][1],
self.postoperative[i][2])
# 将种植体的植入点和跟尖点加入
pSourcePoints.InsertPoint(num, self.ImplantPosition[0][3],
self.ImplantPosition[0][4],
self.ImplantPosition[0][5])
pSourcePoints.InsertPoint(num + 1, self.ImplantPosition[1][3],
self.ImplantPosition[1][4],
self.ImplantPosition[1][5])
pTargetPoints.InsertPoint(num, self.ImplantPosition[0][0],
self.ImplantPosition[0][1],
self.ImplantPosition[0][2])
pTargetPoints.InsertPoint(num + 1, self.ImplantPosition[1][0],
self.ImplantPosition[1][1],
self.ImplantPosition[1][2])
landmarkTransform = vtk.vtkLandmarkTransform()
landmarkTransform.SetSourceLandmarks(pSourcePoints)
landmarkTransform.SetTargetLandmarks(pTargetPoints)
landmarkTransform.SetModeToRigidBody()
landmarkTransform.Update()
matrix = landmarkTransform.GetMatrix()
matrix_np = self.arrayFromVTKMatrix(matrix)
for i in range(4):
for j in range(4):
print("{:10.7f}".format(matrix.GetElement(i, j)), end=", ")
print("")
post_root = np.array([
self.ImplantPosition[1][3], self.ImplantPosition[1][4],
self.ImplantPosition[1][5], 1
])
post_implant = np.array([
self.ImplantPosition[0][3], self.ImplantPosition[0][4],
self.ImplantPosition[0][5], 1
])
# print("术后植入点 ", post_implant)
# print("术后跟尖点 ", post_root)
post_implant = np.matmul(matrix_np, post_implant)
post_root = np.matmul(matrix_np, post_root)
post_implant = post_implant[0:3]
post_root = post_root[0:3]
pre_root = np.array([
self.ImplantPosition[1][0], self.ImplantPosition[1][1],
self.ImplantPosition[1][2]
])
pre_implant = np.array([
self.ImplantPosition[0][0], self.ImplantPosition[0][1],
self.ImplantPosition[0][2]
])
print("术前植入点 ", pre_implant)
print("术前跟尖点 ", pre_root)
print("术后植入点 ", post_implant)
print("术后跟尖点 ", post_root)
print("植入点之间的距离偏差 ", np.linalg.norm(pre_implant - post_implant))
print("根尖点之间的距离偏差 ", np.linalg.norm(pre_root - post_root))
angle = vtk.vtkMath().AngleBetweenVectors(pre_root - pre_implant,
post_root - post_implant)
print("角度偏差 ", math.degrees(angle))
print(Style.RESET_ALL)
def performAffineAndThinPlateRegistration(self, state, landmarks):
"""Perform Affine registration first, use the transformed result as the input of the thin plate transform"""
# if state.transformed:
# if state.transformed.GetTransformNodeID() != state.transform.GetID():
# state.transformed.SetAndObserveTransformNodeID(state.transform.GetID())
volumeNodes = (state.fixed, state.moving)
fiducialNodes = (state.fixedFiducials,state.movingFiducials)
points = state.logic.vtkPointsForVolumes( volumeNodes, fiducialNodes )
#yingli debug
#print 'self.linearMode',self.linearMode
if not self.landmarkTransform:
self.landmarkTransform = vtk.vtkLandmarkTransform()
if self.linearMode == 'Rigid':
self.landmarkTransform.SetModeToRigidBody()
if self.linearMode == 'Similarity':
self.landmarkTransform.SetModeToSimilarity()
if self.linearMode == 'Affine':
self.landmarkTransform.SetModeToAffine()
if state.fixedFiducials.GetNumberOfFiducials() < 3:
self.landmarkTransform.SetModeToRigidBody()
self.landmarkTransform.SetSourceLandmarks(points[state.moving])
self.landmarkTransform.SetTargetLandmarks(points[state.fixed])
self.landmarkTransform.Update()
#transform moving landmarks
affine_transformed_moving_points = vtk.vtkPoints()
self.landmarkTransform.TransformPoints(points[state.moving],affine_transformed_moving_points)
#yingli debug
#print self.landmarkTransform.GetMatrix()
#print 'old moving', points[state.moving].GetPoint(0)
#print 'new moving', affine_transformed_moving_points.GetPoint(0)
# do thin plate, use affine transformed result as the input
# since this is a resample transform, source is the fixed (resampling target) space
# and moving is the target space
if not self.thinPlateTransform:
self.thinPlateTransform = vtk.vtkThinPlateSplineTransform()
self.thinPlateTransform.SetBasisToR() # for 3D transform
self.thinPlateTransform.SetSourceLandmarks(affine_transformed_moving_points)
self.thinPlateTransform.SetTargetLandmarks(points[state.fixed])
self.thinPlateTransform.Update()
if points[state.moving].GetNumberOfPoints() != points[state.fixed].GetNumberOfPoints():
raise hell
#add nesting transfrom: order matters!
transformSelector = slicer.qMRMLNodeComboBox()
transformSelector.nodeTypes = ( ("vtkMRMLTransformNode"), "" )
transformSelector.selectNodeUponCreation = True
transformSelector.addEnabled = True
transformSelector.removeEnabled = True
transformSelector.noneEnabled = True
transformSelector.showHidden = False
transformSelector.showChildNodeTypes = False
transformSelector.setMRMLScene( slicer.mrmlScene )
transformSelector.setToolTip( "The transform for linear registration" )
transformSelector.enabled = False
# concatenate transfroms: method 1: add nesting transfrom: order matters!
# note: this method will keep each transform(not ideal)
# landmarkTransformNode = slicer.util.getNode('Affine-Transform')
# if not landmarkTransformNode:
# landmarkTransformNode=transformSelector.addNode()
# landmarkTransformNode.SetName('Affine-Transform')
# state.transform.SetAndObserveTransformNodeID(landmarkTransformNode.GetID())
# landmarkTransformNode.ApplyTransform(self.landmarkTransform)
# thinPlateTransformNode = slicer.util.getNode('ThinPlate-Transform')
# if not thinPlateTransformNode:
# thinPlateTransformNode=transformSelector.addNode()
# thinPlateTransformNode.SetName('ThinPlate-Transform')
# landmarkTransformNode.SetAndObserveTransformNodeID(thinPlateTransformNode.GetID())
# # thinPlateTransformNode.ApplyTransform(self.thinPlateTransform)
#state.transform.SetAndObserveTransformToParent(self.landmarkTransform)
# #state.transform.SetAndObserveTransformToParent(self.thinPlateTransform)
# stateTransformNodeNode = slicer.util.getNode('Transform')
# stateTransformNodeNode.SetAndObserveTransformToParent(self.thinPlateTransform)
#test vtk concatenate
#self.landmarkTransform.Concatenate(self.landmarkTransform)
#state.transform.SetAndObserveTransformToParent(self.thinPlateTransform)
#concatenate transfroms: method 2: use vtkGeneralTransform to concatenate transfroms.
transform = vtk.vtkGeneralTransform()
transform.Concatenate(self.thinPlateTransform)
transform.Concatenate(self.landmarkTransform)
state.transform.SetAndObserveTransformToParent(transform)
def ComputeCalibration(self, usCalibrationNode, listNode,
eventid): #Ignore listnode and eventid
if (usCalibrationNode is None):
return
markedPointsList = usCalibrationNode.GetNodeReference(
ImagelessUSCalibrationWidget.MARKED_POINTS_ROLE)
unmarkedPointsList = usCalibrationNode.GetNodeReference(
ImagelessUSCalibrationWidget.UNMARKED_POINTS_ROLE)
if (markedPointsList is None or unmarkedPointsList is None):
return
if (markedPointsList.GetNumberOfFiducials() < 2):
usCalibrationNode.SetAttribute(
ImagelessUSCalibrationWidget.OUTPUT_MESSAGE_ROLE,
"Insufficient number of marked corner points selected.")
return
if (unmarkedPointsList.GetNumberOfFiducials() < 2):
usCalibrationNode.SetAttribute(
ImagelessUSCalibrationWidget.OUTPUT_MESSAGE_ROLE,
"Insufficient number of unmarked corner points selected.")
return
# Assume the ordering of points is:
# Unmarked near, marked near, unmarked far, marked far
# Find the points in the probe coordinate system
markedCorner1 = [0, 0, 0]
markedPointsList.GetNthFiducialPosition(0, markedCorner1)
markedCorner2 = [0, 0, 0]
markedPointsList.GetNthFiducialPosition(1, markedCorner2)
unmarkedCorner1 = [0, 0, 0]
unmarkedPointsList.GetNthFiducialPosition(0, unmarkedCorner1)
unmarkedCorner2 = [0, 0, 0]
unmarkedPointsList.GetNthFiducialPosition(1, unmarkedCorner2)
# Find the near points
markedNearPoint = [0, 0, 0]
vtk.vtkMath.Add(markedCorner1, markedCorner2, markedNearPoint)
vtk.vtkMath.MultiplyScalar(markedNearPoint, 0.5)
unmarkedNearPoint = [0, 0, 0]
vtk.vtkMath.Add(unmarkedCorner1, unmarkedCorner2, unmarkedNearPoint)
vtk.vtkMath.MultiplyScalar(unmarkedNearPoint, 0.5)
# Find the vector required for computing the far points
markedUnmarkedVector = [0, 0, 0]
vtk.vtkMath.Subtract(unmarkedNearPoint, markedNearPoint,
markedUnmarkedVector)
markedCornerVector = [0, 0, 0]
vtk.vtkMath.Subtract(markedCorner2, markedCorner1, markedCornerVector)
unmarkedCornerVector = [0, 0, 0]
vtk.vtkMath.Subtract(unmarkedCorner2, unmarkedCorner1,
unmarkedCornerVector)
markedFarVector = [0, 0, 0]
vtk.vtkMath.Cross(markedUnmarkedVector, markedCornerVector,
markedFarVector)
vtk.vtkMath.Normalize(markedFarVector)
unmarkedFarVector = [0, 0, 0]
vtk.vtkMath.Cross(markedUnmarkedVector, unmarkedCornerVector,
unmarkedFarVector)
vtk.vtkMath.Normalize(unmarkedFarVector)
# Compute the far points
try:
depth = float(
usCalibrationNode.GetAttribute(
ImagelessUSCalibrationWidget.DEPTH_ROLE))
except TypeError:
usCalibrationNode.SetAttribute(
ImagelessUSCalibrationWidget.OUTPUT_MESSAGE_ROLE,
"Depth improperly specified.")
return
vtk.vtkMath.MultiplyScalar(markedFarVector, depth)
markedFarPoint = [0, 0, 0]
vtk.vtkMath.Add(markedNearPoint, markedFarVector, markedFarPoint)
vtk.vtkMath.MultiplyScalar(unmarkedFarVector, depth)
unmarkedFarPoint = [0, 0, 0]
vtk.vtkMath.Add(unmarkedNearPoint, unmarkedFarVector, unmarkedFarPoint)
# Now, we can assemble the probe points
probePoints = vtk.vtkPoints()
probePoints.InsertNextPoint(unmarkedNearPoint)
probePoints.InsertNextPoint(markedNearPoint)
probePoints.InsertNextPoint(unmarkedFarPoint)
probePoints.InsertNextPoint(markedFarPoint)
# Compute the scaling factor
usImageNode = usCalibrationNode.GetNodeReference(
ImagelessUSCalibrationWidget.ULTRASOUND_IMAGE_ROLE)
if (usImageNode is None or usImageNode.GetImageData() is None):
usCalibrationNode.SetAttribute(
ImagelessUSCalibrationWidget.OUTPUT_MESSAGE_ROLE,
"No ultrasound image is selected.")
return
# The scale is the ratio of depth to y pixels
usImageDimensions = [0, 0, 0]
usImageNode.GetImageData().GetDimensions(usImageDimensions)
pixelsToMmScale = depth / usImageDimensions[1] # y dimension
imagePixelToImageMm = vtk.vtkTransform()
imagePixelToImageMm.Scale(
[pixelsToMmScale, pixelsToMmScale,
pixelsToMmScale]) # Uniform scaling - similarity transform
print pixelsToMmScale
# Next, we can assembla the image points
imagePoints_ImageMm = vtk.vtkPoints()
imagePoints_ImageMm.InsertNextPoint([0, 0, 0])
imagePoints_ImageMm.InsertNextPoint(
[usImageDimensions[0] * pixelsToMmScale, 0, 0])
imagePoints_ImageMm.InsertNextPoint([0, depth, 0])
imagePoints_ImageMm.InsertNextPoint(
[usImageDimensions[0] * pixelsToMmScale, depth, 0])
# Compute the transform (without the scaling)
imageToProbeTransformNode = usCalibrationNode.GetNodeReference(
ImagelessUSCalibrationWidget.IMAGE_TO_PROBE_TRANSFORM_ROLE)
if (imageToProbeTransformNode is None):
usCalibrationNode.SetAttribute(
ImagelessUSCalibrationWidget.OUTPUT_MESSAGE_ROLE,
"No output ImageToProbe transform specified.")
return
imageMmToProbe = vtk.vtkLandmarkTransform()
imageMmToProbe.SetSourceLandmarks(imagePoints_ImageMm)
imageMmToProbe.SetTargetLandmarks(probePoints)
imageMmToProbe.SetModeToRigidBody()
imageMmToProbe.Update()
# The overall ImageToProbe = ImageMmToProbe * ImagePixelToImageMm
imageToProbeTransform = vtk.vtkTransform()
imageToProbeTransform.PreMultiply()
imageToProbeTransform.Concatenate(imageMmToProbe)
imageToProbeTransform.Concatenate(imagePixelToImageMm)
imageToProbeMatrix = vtk.vtkMatrix4x4()
imageToProbeTransform.GetMatrix(imageToProbeMatrix)
imageToProbeTransformNode.SetMatrixTransformToParent(
imageToProbeMatrix)
usCalibrationNode.SetAttribute(
ImagelessUSCalibrationWidget.OUTPUT_MESSAGE_ROLE, "Success!")
def GetApplicatorTransform(pointtip,pointentry,SourceLandmarkFileName, TargetLandmarkFileName ):
ApplicatorTipLength = .011 #m
# template applicator center at coordinate (0, 0., 0. ) m
# template applicator distal ends at coordinates (0, 0.,+/- ApplicatorTipLength/2. ) m
originalOrientation = vtk.vtkPoints()
originalOrientation.SetNumberOfPoints(2)
originalOrientation.SetPoint(0,0.,0., 0. )
originalOrientation.SetPoint(1,0.,0., ApplicatorTipLength/2.)
slicerLength = numpy.linalg.norm( numpy.array(pointentry) - numpy.array(pointtip) )
unitdirection = 1./slicerLength * (numpy.array(pointentry) - numpy.array(pointtip) )
pointscaled = pointtip + ApplicatorTipLength/2. * unitdirection
print "points", pointentry, pointtip, pointscaled, slicerLength, numpy.linalg.norm( unitdirection ), numpy.linalg.norm( pointscaled - pointtip )
slicerOrientation = vtk.vtkPoints()
slicerOrientation.SetNumberOfPoints(2)
slicerOrientation.SetPoint(0,pointscaled[0],pointscaled[1],pointscaled[2] )
slicerOrientation.SetPoint(1,pointtip[ 0],pointtip[ 1],pointtip[ 2] )
# write landmarks to file
WriteVTKPoints(originalOrientation,SourceLandmarkFileName)
WriteVTKPoints(slicerOrientation ,TargetLandmarkFileName)
ApplicatorLineTransform = vtk.vtkLandmarkTransform()
ApplicatorLineTransform.SetModeToRigidBody()
ApplicatorLineTransform.SetSourceLandmarks(originalOrientation)
ApplicatorLineTransform.SetTargetLandmarks(slicerOrientation )
ApplicatorLineTransform.Update()
print ApplicatorLineTransform.GetMatrix()
# create model of applicator
ApplicatorLength = .10 #m
vtkCylinder = vtk.vtkCylinderSource()
vtkCylinder.SetHeight( ApplicatorLength );
vtkCylinder.SetRadius( .00075 );
vtkCylinder.SetCenter(0.0, 0.0, 0.0 );
vtkCylinder.SetResolution(16);
vtkCylinder.SetCapping(1);
# model orientation
modelOrientation = vtk.vtkPoints()
modelOrientation.SetNumberOfPoints(2)
modelOrientation.SetPoint(0, 0., 0. ,0. )
modelOrientation.SetPoint(1, 0.,-ApplicatorLength/2.,0. )
ModelLineTransform = vtk.vtkLandmarkTransform()
ModelLineTransform.SetModeToRigidBody()
ModelLineTransform.SetSourceLandmarks(modelOrientation )
ModelLineTransform.SetTargetLandmarks(slicerOrientation )
ModelLineTransform.Update()
print ModelLineTransform.GetMatrix()
# transform
slicertransformFilter = vtk.vtkTransformFilter()
slicertransformFilter.SetInput(vtkCylinder.GetOutput() )
slicertransformFilter.SetTransform( ModelLineTransform )
slicertransformFilter.Update()
apppolyData=slicertransformFilter.GetOutput();
# write model to file
vtkModelWriter = vtk.vtkDataSetWriter()
vtkModelWriter.SetInput(apppolyData)
vtkModelWriter.SetFileName("applicator.vtk")
vtkModelWriter.SetFileTypeToBinary()
vtkModelWriter.Write()
# return transform
return ApplicatorLineTransform
def ICP(args):
# This method takes one source surface files and ICP align it to a set of target surfaces.
targetNameList = args[0] # List of target names
sourceSurfaceFile = args[1] # name and full path of the source surface.
dirSurface = args[2] # Path of the surface files.
dirOutputSurface = args[3] # Output path the aligned source surfaces.
dirLandmark = args[4] #Path of the landmark files
sourceLandmarkFile = args[5]
dirOutputLandmarks = args[6]
sourceName = sourceSurfaceFile.split('\\')[-1][:-4]
#sourceSurfaceFile = os.path.join(dirSurface,sourceName + '.vtk')
targetSurfaceFile = os.path.join(dirSurface, targetNameList + '.vtk')
filename = os.path.join(dirOutputSurface, targetNameList + '.vtk')
# Reading surfaces
reader = vtk.vtkPolyDataReader()
reader.SetFileName(sourceSurfaceFile)
reader.Update()
sourceSurface = reader.GetOutput()
reader = vtk.vtkPolyDataReader()
reader.SetFileName(targetSurfaceFile)
reader.Update()
targetSurface = reader.GetOutput()
if targetSurface.GetNumberOfPoints() < 1:
print('Could not read', targetSurfaceFile)
return
#------------------------------------------------------------------------------------------------
# Reading landmarks
targetLandmarkFile = os.path.join(dirLandmark, targetNameList + '.txt')
targetLandmarks = ((np.loadtxt(targetLandmarkFile, skiprows=2)))
if not os.path.isfile(sourceLandmarkFile):
print('\nSource Surface: %s has no landmarks file' % sourceName)
return np.float64(), np.float64()
sourceLandmarks = ((np.loadtxt(sourceLandmarkFile, skiprows=2)))
numberOfLandmarks = np.size(targetLandmarks, 0)
# Set points in vtk
sourcePoints = vtk.vtkPoints()
for point in sourceLandmarks:
sourcePoints.InsertNextPoint(point)
source = vtk.vtkPolyData()
source.SetPoints(sourcePoints)
targetPoints = vtk.vtkPoints()
for point in targetLandmarks:
targetPoints.InsertNextPoint(point)
target = vtk.vtkPolyData()
target.SetPoints(targetPoints)
#------------------------------------------------------------------------------------------------
# Find landmark transformation
landmarkTransform = vtk.vtkLandmarkTransform()
landmarkTransform.SetSourceLandmarks(sourcePoints)
landmarkTransform.SetTargetLandmarks(targetPoints)
landmarkTransform.SetModeToSimilarity()
landmarkTransform.Update()
# Apply landmarks transformation to source surface
TransformFilter = vtk.vtkTransformPolyDataFilter()
TransformFilter.SetInputData(sourceSurface)
TransformFilter.SetTransform(landmarkTransform)
TransformFilter.Update()
transformedSourceSurface = TransformFilter.GetOutput()
# Apply landmarks transformation to source landmarks
TransformFilter = vtk.vtkTransformPolyDataFilter()
TransformFilter.SetInputData(source)
TransformFilter.SetTransform(landmarkTransform)
TransformFilter.Update()
transformedSourceLandmarks = TransformFilter.GetOutput()
#------------------------------------------------------------------------------------------------
# Find icp transformation
icp = vtk.vtkIterativeClosestPointTransform()
icp.SetSource(transformedSourceSurface)
icp.SetTarget(targetSurface)
icp.GetLandmarkTransform().SetModeToRigidBody()
icp.Modified()
icp.Update()
#------------------------------------------------------------------------------------------------
# Apply icp transformation to transformed source surface
TransformFilter = vtk.vtkTransformPolyDataFilter()
TransformFilter.SetInputData(transformedSourceSurface)
TransformFilter.SetTransform(icp)
TransformFilter.Update()
icptransformedSourceSurface = TransformFilter.GetOutput()
# Apply icp transformation to transformed source landmarks
TransformFilter = vtk.vtkTransformPolyDataFilter()
TransformFilter.SetInputData(transformedSourceLandmarks)
TransformFilter.SetTransform(icp)
TransformFilter.Update()
icptransformedSourceLandmarks = TransformFilter.GetOutput()
#===========================================================================
# RMS_transformedSurface = Metrics.RMS(icptransformedSourceSurface,targetSurface,VTKobj=True)
# RMS_SourceTarget = Metrics.RMS(sourceSurface,targetSurface,VTKobj=True)
#===========================================================================
#------------------------------------------------------------------------------------------------
# Write transformed source surface to .vtk file
writer = vtk.vtkPolyDataWriter()
writer.SetInputData(icptransformedSourceSurface)
#writer.SetInputData(transformedSourceSurface)
writer.SetFileName(filename)
writer.Write()
# Write transformed landmarks to .txt file readable by elastix
npTranformedLandmarks = np.zeros([numberOfLandmarks, 3])
for index in range(numberOfLandmarks):
point = [0, 0, 0]
icptransformedSourceLandmarks.GetPoint(index, point)
#transformedSourceLandmarks.GetPoint(index, point)
npTranformedLandmarks[index, :] = point
filename = os.path.join(dirOutputLandmarks, targetNameList + '.txt')
with open(filename, 'w+') as f:
f.write('point\n')
f.write(str(numberOfLandmarks))
for idx in range(numberOfLandmarks):
f.write('\n' + str(npTranformedLandmarks[idx, 0]) + ' ')
for Val in npTranformedLandmarks[idx, 1:]:
f.write(str(Val) + ' ')
def register(self, fixedData, movingData, index = -1, discard = False, delta = 0, fov = 9999999.0,
down_fix = 1, down_mov = 1, occ = 9999999.0, op = False, useMask = False, isTime = False, MaxRate = 0.2,
aug = False, distance_fix = 0.3, distance_mov = 0.1):
time1 = time.time()
if index == -1:
index = self.gui.getDataIndex({'Contour': 0, 'Centerline': 1}, 'Select the object')
if index is None:
return None, None, None
if index == 0:
fixed_points = fixedData.getPointSet('Contour').copy()
moving_points = movingData.getPointSet('Contour').copy()
else:
fixed_points = fixedData.getPointSet('Centerline').copy()
moving_points = movingData.getPointSet('Centerline').copy()
fixed_bif = db.getBifurcation(fixed_points)
moving_bif = db.getBifurcation(moving_points)
if useMask:
mask_points = movingData.getPointSet('Mask')
for point in mask_points:
moving_points = npy.delete(moving_points, npy.where((npy.abs(moving_points[:, 2] - point[2]) < 0.0001) & (npy.round(moving_points[:, -1]) == point[3])), axis = 0)
fixed_res = fixedData.getResolution().tolist()
moving_res = movingData.getResolution().tolist()
fixed_points = fixed_points[npy.where(fixed_points[:, 0] >= 0)]
moving_points = moving_points[npy.where(moving_points[:, 0] >= 0)]
# Use the bifurcation as the initial position
if (fixed_bif < 0) or (moving_bif < 0):
fixed_min = 0
# Augmentation of pointset
fixed = fixed_points.copy()
moving = moving_points.copy()
if index == 1 and aug:
fixed = util.augmentCenterline(fixed, 1, 10)
moving = util.augmentCenterline(moving, 1, 10)
fix_dis = util.getAxisSin(fixed, 3 / fixed_res[2]) * distance_fix
mov_dis = util.getAxisSin(moving, 3 / moving_res[2]) * distance_mov
fixed = util.resampleCenterline(fixed, fix_dis / fixed_res[2])
moving = util.resampleCenterline(moving, mov_dis / moving_res[2])
fixed = fixed[npy.cast[npy.int32](npy.abs(fixed[:, 2] - fixed_bif)) % down_fix == 0]
moving = moving[npy.cast[npy.int32](npy.abs(moving[:, 2] - moving_bif)) % down_mov == 0]
fixed[:, :3] *= fixed_res[:3]
moving[:, :3] *= moving_res[:3]
if (fixed_bif >= 0) and (moving_bif >= 0):
fixed[:, 2] -= (fixed_bif * fixed_res[2] - moving_bif * moving_res[2] + delta)
# Prepare for ICP
LandmarkTransform = vtk.vtkLandmarkTransform()
LandmarkTransform.SetModeToRigidBody()
MaxIterNum = 50
#MaxNum = 600
MaxNum = int(MaxRate * moving.shape[0] + 0.5)
targetPoints = [vtk.vtkPoints(), vtk.vtkPoints(), vtk.vtkPoints()]
targetVertices = [vtk.vtkCellArray(), vtk.vtkCellArray(), vtk.vtkCellArray()]
target = [vtk.vtkPolyData(), vtk.vtkPolyData(), vtk.vtkPolyData()]
Locator = [vtk.vtkCellLocator(), vtk.vtkCellLocator(), vtk.vtkCellLocator()]
if index == 0:
if not op:
label_dis = [3, 3, 3]
else:
label_dis = [3, 2, 1]
else:
if op:
label_dis = [3, 3, 3]
else:
label_dis = [3, 2, 1]
for i in range(3):
for x in fixed[npy.round(fixed[:, 3]) != label_dis[i]]:
id = targetPoints[i].InsertNextPoint(x[0], x[1], x[2])
targetVertices[i].InsertNextCell(1)
targetVertices[i].InsertCellPoint(id)
target[i].SetPoints(targetPoints[i])
target[i].SetVerts(targetVertices[i])
Locator[i].SetDataSet(target[i])
Locator[i].SetNumberOfCellsPerBucket(1)
Locator[i].BuildLocator()
step = 1
if moving.shape[0] > MaxNum:
ind = moving[:, 2].argsort()
moving = moving[ind, :]
step = moving.shape[0] / MaxNum
nb_points = moving.shape[0] / step
accumulate = vtk.vtkTransform()
accumulate.PostMultiply()
points1 = vtk.vtkPoints()
points1.SetNumberOfPoints(nb_points)
label = npy.zeros([MaxNum * 2], dtype = npy.int8)
j = 0
for i in range(nb_points):
points1.SetPoint(i, moving[j][0], moving[j][1], moving[j][2])
label[i] = moving[j][3]
j += step
closestp = vtk.vtkPoints()
closestp.SetNumberOfPoints(nb_points)
points2 = vtk.vtkPoints()
points2.SetNumberOfPoints(nb_points)
id1 = id2 = vtk.mutable(0)
dist = vtk.mutable(0.0)
outPoint = [0.0, 0.0, 0.0]
p1 = [0.0, 0.0, 0.0]
p2 = [0.0, 0.0, 0.0]
iternum = 0
a = points1
b = points2
'''
path = sys.argv[0]
if os.path.isfile(path):
path = os.path.dirname(path)
path += '/Data/Transform'
wfile = open("%s/transform.txt" % path, 'w')
matrix = accumulate.GetMatrix()
T = ml.mat([matrix.GetElement(0, 3), matrix.GetElement(1, 3), matrix.GetElement(2, 3)]).T;
R = ml.mat([[matrix.GetElement(0, 0), matrix.GetElement(0, 1), matrix.GetElement(0, 2)],
[matrix.GetElement(1, 0), matrix.GetElement(1, 1), matrix.GetElement(1, 2)],
[matrix.GetElement(2, 0), matrix.GetElement(2, 1), matrix.GetElement(2, 2)]]).I
if (fixed_bif >= 0) and (moving_bif >= 0):
T[2] += (fixed_bif * fixed_res[2] - moving_bif * moving_res[2] + delta)
saveTransform(wfile, T, R)
'''
while True:
for i in range(nb_points):
Locator[label[i]].FindClosestPoint(a.GetPoint(i), outPoint, id1, id2, dist)
closestp.SetPoint(i, outPoint)
LandmarkTransform.SetSourceLandmarks(a)
LandmarkTransform.SetTargetLandmarks(closestp)
LandmarkTransform.Update()
accumulate.Concatenate(LandmarkTransform.GetMatrix())
iternum += 1
if iternum >= MaxIterNum:
break
dist_err = 0
for i in range(nb_points):
a.GetPoint(i, p1)
LandmarkTransform.InternalTransformPoint(p1, p2)
b.SetPoint(i, p2)
dist_err += npy.sqrt((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2 + (p1[2] - p2[2]) ** 2)
dist_err /= nb_points
print "iter = %d: %f" % (iternum, dist_err)
'''
matrix = accumulate.GetMatrix()
T = ml.mat([matrix.GetElement(0, 3), matrix.GetElement(1, 3), matrix.GetElement(2, 3)]).T;
R = ml.mat([[matrix.GetElement(0, 0), matrix.GetElement(0, 1), matrix.GetElement(0, 2)],
[matrix.GetElement(1, 0), matrix.GetElement(1, 1), matrix.GetElement(1, 2)],
[matrix.GetElement(2, 0), matrix.GetElement(2, 1), matrix.GetElement(2, 2)]]).I;
if (fixed_bif >= 0) and (moving_bif >= 0):
T[2] += (fixed_bif * fixed_res[2] - moving_bif * moving_res[2])
saveTransform(wfile, T, R)
'''
b, a = a, b
time2 = time.time()
#wfile.close()
# Get the result transformation parameters
matrix = accumulate.GetMatrix()
T = ml.mat([matrix.GetElement(0, 3), matrix.GetElement(1, 3), matrix.GetElement(2, 3)]).T
R = ml.mat([[matrix.GetElement(0, 0), matrix.GetElement(0, 1), matrix.GetElement(0, 2)],
[matrix.GetElement(1, 0), matrix.GetElement(1, 1), matrix.GetElement(1, 2)],
[matrix.GetElement(2, 0), matrix.GetElement(2, 1), matrix.GetElement(2, 2)]]).I
#T = ml.mat([0, 0, 0]).T
#R = ml.mat([[1, 0, 0], [0, 1, 0], [0, 0, 1]]).T
if (fixed_bif >= 0) and (moving_bif >= 0):
T[2] += (fixed_bif * fixed_res[2] - moving_bif * moving_res[2] + delta)
# Resample the moving contour
moving_points = movingData.getPointSet('Contour').copy()
moving_center = movingData.getPointSet('Centerline').copy()
#new_trans_points, result_center_points = util.resliceTheResultPoints(moving_points, moving_center, 20, moving_res, fixed_res, discard, R, T)
new_trans_points, result_center_points = moving_points, moving_center
result_center_points[:, :3] = util.applyTransformForPoints(result_center_points[:, :3], moving_res, fixed_res, R, T, ml.zeros([3, 1], dtype = npy.float32))
new_trans_points[:, :3] = util.applyTransformForPoints(new_trans_points[:, :3], moving_res, fixed_res, R, T, ml.zeros([3, 1], dtype = npy.float32))
T = -T
T = R * T
transform = sitk.Transform(3, sitk.sitkAffine)
para = R.reshape(1, -1).tolist()[0] + T.T.tolist()[0]
transform.SetParameters(para)
movingImage = movingData.getSimpleITKImage()
fixedImage = fixedData.getSimpleITKImage()
resultImage = sitk.Resample(movingImage, fixedImage, transform, sitk.sitkLinear, 0, sitk.sitkFloat32)
if isTime:
return sitk.GetArrayFromImage(resultImage), {'Contour': new_trans_points, 'Centerline': result_center_points}, para + [0, 0, 0], time2 - time1
return sitk.GetArrayFromImage(resultImage), {'Contour': new_trans_points, 'Centerline': result_center_points}, para + [0, 0, 0]
def createMorph(selectedImages,selectedPMs):
"""
Translates and rotate the bitmaps based on the shapedefining landmarks (selectedPMs)
of the associated image to the target image (first image).
Morphs the result so that the bitmap overlay on the first image is valid for the first image.
"""
#save the temporary results here later:
os_temp_path = tempfile.gettempdir()
#get the measurements for the first image (our targets)
mainImage = OriginalImage.objects.all().get(id=selectedImages[0])
potentialids = []
#now get the associated measurements
measures = Measurement.objects.all().filter(id__in=selectedPMs[0]).filter(mogelijkemeting__shapedefining=True)
measures = [j for j in measures]
measures.sort(key=lambda x: x.mogelijkemeting.name)
coordsx = []
coordsy = []
for k, measurement in enumerate(measures):
coordsx.append(float(measurement.x))
coordsy.append(float(measurement.y))
potentialids.append(measurement.mogelijkemeting.id)
r1 = vtk.vtkJPEGReader()
r1.SetFileName(settings.DATADIR + mainImage.id + ".jpg")
r1.Update()
# flip y coord (VTK has opposite convention), create 3-d coords (z=0)
ydim = r1.GetOutput().GetDimensions()[1]
coords = [(x, ydim - y, 0) for (x,y) in zip(coordsx, coordsy)]
# convert everything to vtkPoints
lmt = vtk.vtkPoints()
lmt.SetNumberOfPoints(len(coords))
for i, coord in enumerate(coords):
lmt.SetPoint(i,coord)
#The target is clear, let's get to work, get the source images...
images = []
#we don't need the first image or its measures anymore, because they don't need to be transformed or morphed
selectedImages.pop(0)
selectedPMs.pop(0)
for id in selectedImages:
images.append(OriginalImage.objects.all().get(id=id))
transformations = []
morphtransformations = []
#Create a new database object for the target image to associate the bitmaps with
img = OriginalImage(project=mainImage.project, name='MorphedImage')
img.save()
imp = Image.open(settings.DATADIR + mainImage.id + '.jpg')
imp.save(settings.DATADIR + img.id + '.jpg', 'JPEG')
orig_bitmaps = Bitmap.objects.all().filter(image=mainImage)
for bm in orig_bitmaps:
#store bitmaps of mainImage as sub of img
bitmap = Bitmap(project=img.project, name='warpedbitmap', image=img,
mogelijkemeting=bm.mogelijkemeting, imagewidth=bm.imagewidth,
imageheight=bm.imageheight, minx=bm.minx, miny=bm.miny, maxx=bm.maxx, maxy=bm.maxy)
bitmap.save()
bitmap_image = Image.open(settings.DATADIR + bm.id + '.gif')
bitmap_image = bitmap_image.convert("RGBA")
bitmap_image.save(settings.DATADIR + bitmap.id + '.gif', transparency=0)
#now get the other images and perform our transformations
for i in range(len(images)):
measures = Measurement.objects.all().filter(id__in=selectedPMs[i]).filter(mogelijkemeting__shapedefining=True)#get measurements
measures = [j for j in measures]
measures.sort(key=lambda x: x.mogelijkemeting.name)
coordsx = []
coordsy = []
for k, measurement in enumerate(measures):
coordsx.append(float(measurement.x))
coordsy.append(float(measurement.y))
if potentialids[k] != measurement.mogelijkemeting.id: #the potentialmeasurements do not match up to the ones in the target image
return img, 0
r = vtk.vtkJPEGReader()
r.SetFileName(settings.DATADIR + images[i].id + ".jpg")
r.Update()
ydim = r.GetOutput().GetDimensions()[1]
coordso = [(x, ydim - y, 0) for (x,y) in zip(coordsx, coordsy)]
lms = vtk.vtkPoints()
lms.SetNumberOfPoints(len(coordso))
for k, coord in enumerate(coordso):
lms.SetPoint(k,coord)
transformation = vtk.vtkLandmarkTransform()
transformation.SetTargetLandmarks(lmt)
lmt.Modified()
transformation.SetSourceLandmarks(lms)
lms.Modified()
#size matters, so set the mode to Rigid Body (also known as do not scale please)
transformation.SetModeToRigidBody()
transformation.Inverse()
transformation.Update()
out = vtk.vtkPoints()#this will be the source of our morph transform
transformation.TransformPoints(lms,out)
transformations.append(transformation)
ir = vtk.vtkImageReslice()
# we're not using linear, because we want to improve the quality of the bitmaps
ir.SetInterpolationModeToNearestNeighbor()
ir.SetResliceTransform(transformation)
ir.SetInput(r.GetOutput())
ir.SetInformationInput(r1.GetOutput())
w = vtk.vtkJPEGWriter()
w.SetFileName(os_temp_path+'/translated'+images[i].id+'.jpg')
w.SetInput(ir.GetOutput())
w.Write()
r2 = vtk.vtkJPEGReader()
r2.SetFileName(os_temp_path+'/translated'+images[i].id+'.jpg')
r2.Update()
# the mighty morphing ThinPlateSplineTransform
morphtransform = vtk.vtkThinPlateSplineTransform()
morphtransform.SetBasisToR2LogR()
morphtransform.SetSourceLandmarks(lms)
lms.Modified()
morphtransform.SetTargetLandmarks(lmt)
lmt.Modified()
morphtransform.Inverse()
morphtransform.Update()
morphtransformations.append(morphtransform)
#ir.SetInput(r2.GetOutput())
#ir.SetInformationInput(r1.GetOutput())
bitmaps = Bitmap.objects.all().filter(image=images[i])
#now perform the total transformation on all bitmaps
for bm in bitmaps:
location = settings.DATADIR + bm.id + ".gif"
im = Image.open(location)
im = im.convert("RGBA")
im.save(settings.DATADIR + bm.id + ".png", "PNG")
r3 = vtk.vtkPNGReader()
r3.SetFileName(settings.DATADIR + bm.id + '.png')
r3.Update()
ir2 = vtk.vtkImageReslice()
ir2.SetInterpolationModeToNearestNeighbor()
ir2.SetResliceTransform(morphtransform)
ir2.SetInput(r3.GetOutput())
ir2.SetInformationInput(r2.GetOutput())
w3 = vtk.vtkPNGWriter()
w3.SetFileName(os_temp_path+'/morphed'+bm.id+'.png')
w3.SetInput(ir2.GetOutput())
w3.Write()
bitmap = Bitmap(project=img.project, name='warpedbitmap', image=img,
mogelijkemeting=bm.mogelijkemeting, imagewidth=bm.imagewidth,
imageheight=bm.imageheight, minx=bm.minx, miny=bm.miny, maxx=bm.maxx, maxy=bm.maxy)
bitmap.save()
im = Image.open(os_temp_path+'/morphed'+bm.id+'.png')
im = im.convert("RGBA")
im.save(settings.DATADIR + bitmap.id + '.gif', transparency=0)
return img, 1
LandmarkDistanceList = np.array(LandmarkDistanceList)
SubjectList = np.array(SubjectList)
LabelList = np.array(LabelList)
distArrInd = LandmarkDistanceList.argsort()
sortedDistList = LandmarkDistanceList[distArrInd[::-1]]
sortedSubjectList = SubjectList[distArrInd[::-1]]
sortedLabelList = LabelList[distArrInd[::-1]]
sortedCMRepSurfaceList = CMRepSurfaceList[distArrInd[::-1]]
cntFlip = 0
for i in range(len(sortedCMRepSurfaceList)):
dataTest = sortedCMRepSurfaceList[i]
landmarktransformCheck = vtk.vtkLandmarkTransform()
landmarktransformCheck.SetSourceLandmarks(dataTest.GetPoints())
landmarktransformCheck.SetTargetLandmarks(mu.GetPoints())
landmarktransformCheck.SetModeToRigidBody()
landmarktransformCheck.Update()
transformCheck = vtk.vtkTransform()
transformCheck.SetMatrix(landmarktransformCheck.GetMatrix())
transformCheck.Update()
if np.abs(transformCheck.GetOrientation()[0]) >= 90:
print(sortedSubjectList[i])
cntFlip += 1
if np.abs(transformCheck.GetOrientation()[1]) >= 90:
print(sortedSubjectList[i])
cntFlip += 1
