def loadSurface(fname):
reader = vtk.vtkXMLPolyDataReader()
reader.SetFileName(fileName)
reader.Update()
# Take the largest connected component
connectFilter = vtk.vtkPolyDataConnectivityFilter()
connectFilter.SetInputConnection(reader.GetOutputPort())
connectFilter.SetExtractionModeToLargestRegion()
connectFilter.Update()
normals = vtk.vtkPolyDataNormals()
normals.SetInputConnection(connectFilter.GetOutputPort())
normals.Update()
pd = normals.GetOutput()
com = vtk.vtkCenterOfMass()
com.SetInputData(pd)
com.SetUseScalarsAsWeights(False)
com.Update()
center = com.GetCenter()
# Mapper
mapper = vtk.vtkPolyDataMapper()
mapper.SetInputConnection(normals.GetOutputPort())
actor = vtk.vtkActor()
actor.SetMapper(mapper)
prop = actor.GetProperty()
prop.SetColor(vtk.vtkColor3d(hexCol("#873927")))
# Assign actor to the renderer
prop.SetOpacity(0.35)
return actor, center
def centroid(self):
'''average of all vertices'''
center = vtk.vtkCenterOfMass()
center.SetInputData(self.polydata)
center.SetUseScalarsAsWeights(False)
center.Update()
return center.GetCenter()
def calculate_center_of_gravity_vtk(self, ):
'''Function to calculate the center of gravity
.. Note::
The VTK Pytnon bindings must be installed to use this function
Examples:
This example assumes that a mesh has been read by bemio and mesh
data is contained in a `PanelMesh` object called `mesh`
>>> mesh.calculate_center_of_gravity_vtk()
'''
if self.VTK_installed is False:
raise VTK_Exception(
'VTK must be installed to access the calculate_center_of_gravity_vtk function'
)
com = vtk.vtkCenterOfMass()
if vtk.VTK_MAJOR_VERSION >= 6:
com.SetInputData(self.vtp_mesh)
else:
com.SetInput(self.vtp_mesh)
com.Update()
self.center_of_gravity = com.GetCenter()
print 'Calculated center of gravity assuming uniform material density'
def __init__(self, vtk_mesh, center_scale=False, name=None):
center = vtk.vtkCenterOfMass()
center.SetInputData(vtk_mesh)
center.SetUseScalarsAsWeights(False)
center.Update()
self.old_centerpoint = center.GetCenter()
self.centerpoint = center.GetCenter()
self.old_polydata = vtk_mesh #I think that I'm being passed a PolyData now, instead of a vtk_mesh
self.old_scale = np.linalg.norm(
vtk_to_numpy(vtk_mesh.GetPoints().GetData()), 'fro')
if center_scale:
transform = vtk.vtkTransform()
#bp()
transform.Translate(-self.centerpoint[0], -self.centerpoint[1],
-self.centerpoint[2])
transformt = vtk.vtkTransformPolyDataFilter()
transformt.SetInputData(vtk_mesh)
transformt.SetTransform(transform)
transformt.Update()
self.polydata = transformt.GetOutput()
else:
self.polydata = vtk_mesh
self.name = name
def toOriginalPos(actor, center, rotationTransform):
rotMat = vtk.vtkMatrix4x4()
rotationTransform.GetTranspose(rotMat)
rotTrans = vtk.vtkTransform()
rotTrans.SetMatrix(rotMat)
transformFilter = vtk.vtkTransformFilter()
transformFilter.SetInputData(actor.GetMapper().GetInput())
transformFilter.SetTransform(rotTrans)
transformFilter.Update()
mapper = vtk.vtkPolyDataMapper()
mapper.SetInputConnection(transformFilter.GetOutputPort())
mapper.Update()
actor.SetMapper(mapper)
centerTransform = vtk.vtkTransform()
centerTransform.Translate(center[0], center[1], center[2])
transformFilter = vtk.vtkTransformFilter()
transformFilter.SetInputData(actor.GetMapper().GetInput())
transformFilter.SetTransform(centerTransform)
transformFilter.Update()
mapper = vtk.vtkPolyDataMapper()
mapper.SetInputConnection(transformFilter.GetOutputPort())
mapper.Update()
actor.SetMapper(mapper)
centerCalculer = vtk.vtkCenterOfMass()
centerCalculer.SetInputData(actor.GetMapper().GetInput())
centerCalculer.SetUseScalarsAsWeights(False)
centerCalculer.Update()
center = centerCalculer.GetCenter()
print(center)
def get_tangent_vec(contour_id, tangent_vec):
# Export the provided contour to a usable VTK PolyData object.
contour_set = sv.dmg.get_segmentation(contour_group_name)
contour_pd = contour_set.get_segmentation(contour_id).get_polydata()
# Apply a VTK filter to locate the center of mass (average) of the
# points in the first contour.
com_filter = vtk.vtkCenterOfMass()
com_filter.SetInputData(contour_pd)
com_filter.Update()
center = com_filter.GetCenter()
# Save the points in the first contour to a vtkPoints object and then
# extract the first two points.
contour_pts = contour_pd.GetPoints()
point1 = contour_pts.GetPoint(0)
point2 = contour_pts.GetPoint(5)
# Calculate the vector (deltas in x, y, and z) between the center point
# of the contour and two points on the contour.
vec1 = [
point1[0] - center[0], point1[1] - center[1], point1[2] - center[2]
]
vec2 = [
point2[0] - center[0], point2[1] - center[1], point2[2] - center[2]
]
# Calculate the vector cross product of the two vectors, which is also
# the tangent vector to the plane of the two points.
vtk.vtkMath.Cross(vec1, vec2, tangent_vec)
def compute_pre_transformation(self, file_name):
translation = [0, 0, 0]
if self.config['pre-align']['align_center_of_mass']:
# hack to avoid how the objimporter deals with multiple polydata
pd = Utils3D.multi_read_surface(file_name)
if pd.GetNumberOfPoints() < 1:
print('Could not read', file_name)
return None
vtk_cm = vtk.vtkCenterOfMass()
vtk_cm.SetInputData(pd)
vtk_cm.SetUseScalarsAsWeights(False)
vtk_cm.Update()
cm = vtk_cm.GetCenter()
translation = [-cm[0], -cm[1], -cm[2]]
t = vtk.vtkTransform()
t.Identity()
rx = self.config['pre-align']['rot_x']
ry = self.config['pre-align']['rot_y']
rz = self.config['pre-align']['rot_z']
# Scale is handling by doing magic with the view frustrum elsewhere
# s = self.config['pre-align']['scale']
# t.Scale(s, s, s)
t.RotateY(ry)
t.RotateX(rx)
t.RotateZ(rz)
t.Translate(translation)
t.Update()
return t
def read_mesh(file_name, scale):
'''Read a VTK vtu file.
'''
reader = vtk.vtkXMLUnstructuredGridReader()
reader.SetFileName(file_name)
reader.Update()
mesh = reader.GetOutput()
print("Mesh extent: {0:s}".format(str(mesh.GetBounds())))
com_filter = vtk.vtkCenterOfMass()
com_filter.SetInputData(mesh)
com_filter.Update()
center = com_filter.GetCenter()
print("Mesh center: {0:s}".format(str(center)))
transform = vtk.vtkTransform()
transform.Identity()
transform.Scale(scale, scale, scale)
transform.Translate(-center[0], -center[1], -center[2])
transform.Update()
transform_filter = vtk.vtkTransformFilter()
transform_filter.SetInputData(mesh)
transform_filter.SetTransform(transform)
transform_filter.Update()
mesh = transform_filter.GetOutput()
mesh.Modified()
com_filter = vtk.vtkCenterOfMass()
com_filter.SetInputData(mesh)
com_filter.Update()
center = com_filter.GetCenter()
print("New mesh center: {0:s}".format(str(center)))
print("New mesh extent: {0:s}".format(str(mesh.GetBounds())))
# check_nodes(mesh)
#print_connectivity(mesh)
num_points = mesh.GetNumberOfPoints()
points = mesh.GetPoints()
print("Number of points: {0:d}".format(num_points))
num_cells = mesh.GetNumberOfCells()
print("Number of cells: {0:d}".format(num_cells))
cells = mesh.GetCells()
return mesh
def find_centeroid(poly):
'''
Return a 3x tuple
'''
centerMass = vtk.vtkCenterOfMass()
centerMass.SetInputData(poly)
centerMass.SetUseScalarsAsWeights(False)
centerMass.Update()
return centerMass.GetCenter()
def findRadius(name, index):
contour_group_name = name
contour_group_name_in_repo = contour_group_name
contour_ids = [index]
repo_contour_ids = [
contour_group_name_in_repo + "_contour_" + str(id)
for id in contour_ids
]
try:
# Does this item already exist in the Repository?
if int(Repository.Exists(repo_contour_ids[0])):
a = 5
else:
GUI.ExportContourToRepos(contour_group_name, repo_contour_ids)
# Calculate the centers of each contour in the segmentation group with a VTK
# center of mass filter, then calculate the radius of the contour.
contour_radii = []
for id in repo_contour_ids:
# Export the id'th contour to a VTK polyData object.
contour = Repository.ExportToVtk(id)
# Apply a VTK filter to locate the center of mass (average) of the points in the contour.
com_filter = vtk.vtkCenterOfMass()
com_filter.SetInputData(contour)
com_filter.Update()
center = com_filter.GetCenter()
# Save the points in the contour to a vtkPoints object.
contour_pts = contour.GetPoints()
# Iterate through the list of points, but not the last two. (last two are
# control points that bung up the solution)
radii = []
for point_index in range(contour_pts.GetNumberOfPoints() - 2):
# Save the point to a cordinate list.
coord = [0.0, 0.0, 0.0]
contour_pts.GetPoint(point_index, coord)
# Compute the "radius" between the current point and the center of the contour.
# Distance formula: sqrt(dx^2 + dy^2 + dz^2)
radii.append(
math.sqrt(
math.pow(coord[0] - center[0], 2) +
math.pow(coord[1] - center[1], 2) +
math.pow(coord[2] - center[2], 2)))
# Append the average of the "radii" to the list of contour radii as the nominal radius of the current contour.
contour_radii.append(numpy.mean(radii))
return (contour_radii[0])
except Exception as e:
print("Error!" + str(e))
return
def centerOfMass(actor):
'''Get the Center of Mass of the actor'''
if vtkMV: #faster
cmf = vtk.vtkCenterOfMass()
setInput(cmf, polydata(actor, True))
cmf.Update()
c = cmf.GetCenter()
return np.array(c)
else:
pts = coordinates(actor, True)
if not len(pts): return np.array([0, 0, 0])
return np.mean(pts, axis=0)
def calc_centers(self):
""" Calculate the contour centers.
Create a VTK center of mass filter to calculate contour centers.
"""
centers = []
for id in self.repo_contour_ids:
print(id)
contour = Repository.ExportToVtk(id)
com_filter = vtk.vtkCenterOfMass()
com_filter.SetInputData(contour)
com_filter.Update()
center = com_filter.GetCenter()
centers.append(center)
#_for id in self.repo_contor_ids
self.centers = centers
def check_if_filt_tri_inside_PD(tripts, mesh):
points1 =vtk.vtkPoints()
points1.InsertNextPoint (triangle_points[0])
points1.InsertNextPoint (triangle_points[1])
points1.InsertNextPoint (triangle_points[2])
triangle =vtk.vtkTriangle()
triangle.GetPointIds().SetId ( 0, 0 )
triangle.GetPointIds().SetId ( 1, 1 )
triangle.GetPointIds().SetId ( 2, 2 )
triangles = vtk.vtkCellArray()
triangles.InsertNextCell(triangle)
trianglePolyData =vtk.vtkPolyData()
trianglePolyData.SetPoints( points1 )
trianglePolyData.SetPolys( triangles )
A=triangle_points[0]
B=triangle_points[1]
C=triangle_points[2]
a_minus_b=A-B
a_minus_C=A-C
normtoplane=np.cross(a_minus_b,a_minus_C)
centerOfMassFilter =vtk.vtkCenterOfMass()
centerOfMassFilter.SetInputData(trianglePolyData)
centerOfMassFilter.Update()
center=centerOfMassFilter.GetCenter()
plane = vtk.vtkPlane()
plane.SetOrigin(center)
plane.SetNormal(normtoplane)
planeCut = vtk.vtkCutter()
planeCut.SetInputData(mesh)
planeCut.SetCutFunction(plane)
planeCut.Update()
num_inter= planeCut.GetOutput().GetNumberOfPoints()
return num_inter
def GetGeomCenterOfMass(mesh):
cellcenter=vtk.vtkCellCenters()
cellcenter.SetInputData(mesh)
cellcenter.Update()
cell_centeroutput=cellcenter.GetOutput()
cell_centeroutput_num=cell_centeroutput.GetNumberOfPoints()
center=[0.0,0.0,0.0]
centerOfMassFilter =vtk.vtkCenterOfMass()
centerOfMassFilter.SetInputData(mesh)
centerOfMassFilter.SetUseScalarsAsWeights(0)
centerOfMassFilter.Update()
xx=centerOfMassFilter.GetCenter()
return xx,cell_centeroutput
def center_poly_data(poly_data):
centerOfMassFilter = vtk.vtkCenterOfMass()
centerOfMassFilter.SetInputData(poly_data)
centerOfMassFilter.SetUseScalarsAsWeights(False)
centerOfMassFilter.Update()
center = np.array(centerOfMassFilter.GetCenter())
transform = vtk.vtkTransform()
transform.Translate(-center)
transform_filter = vtk.vtkTransformPolyDataFilter()
transform_filter.SetTransform(transform)
transform_filter.SetInputData(poly_data)
transform_filter.Update()
poly_data = transform_filter.GetOutput()
return poly_data
def doubleClickFunction(self, node):
centerList = [0] * 3
# get center position of model/drawing
if isinstance(node, slicer.vtkMRMLModelNode):
pd = node.GetPolyData()
center = vtk.vtkCenterOfMass()
center.SetInputData(pd)
center.Update()
centerList = center.GetCenter()
elif isinstance(node, slicer.vtkMRMLMarkupsCurveNode):
node.GetNthControlPointPosition(
round(node.GetNumberOfControlPoints() / 2), centerList)
elif isinstance(node, slicer.vtkMRMLMarkupsFiducialNode):
node.GetNthFiducialPosition(0, centerList)
else:
return
self.centerPosition(centerList)
def centerCOM(polydata):
# Get Center of Mass
centerFilter = vtk.vtkCenterOfMass()
centerFilter.SetInputData(polydata)
centerFilter.SetUseScalarsAsWeights(False)
centerFilter.Update()
center = centerFilter.GetCenter()
print(center)
# Change Center to (0, 0, 0)
transform = vtk.vtkTransform()
transform.Translate(-center[0], -center[1], -center[2])
transformFilter = vtk.vtkTransformPolyDataFilter()
transformFilter.SetInputData(polydata)
transformFilter.SetTransform(transform)
transformFilter.Update()
centeredPolydata = transformFilter.GetOutput()
return centeredPolydata
def get_face_center(solid, face_id, color=[1, 0, 0]):
'''
Get the center of a solid model face.
'''
model_face = model_name + "_face_" + str(face_id)
solid.get_face_polydata(model_face, face_id)
face_pd = sv.repository.export_to_vtk(model_face)
com_filter = vtk.vtkCenterOfMass()
com_filter.SetInputData(face_pd)
com_filter.Update()
face_center = com_filter.GetCenter()
# Show the face.
face_actor = sv_vis.pRepos(renderer, model_face)[1]
#sv_vis.polyDisplayWireframe(renderer, model_face_2)
face_actor.GetProperty().SetColor(color[0], color[1], color[2])
return face_center
def center_of_mass(self, scalars_weight=False):
"""Return the coordinates for the center of mass of the mesh.
Parameters
----------
scalars_weight : bool, optional
Flag for using the mesh scalars as weights. Defaults to False.
Return
------
center : np.ndarray, float
Coordinates for the center of mass.
"""
alg = vtk.vtkCenterOfMass()
alg.SetInputDataObject(self)
alg.SetUseScalarsAsWeights(scalars_weight)
alg.Update()
return np.array(alg.GetCenter())
def information(poly):
# get the maximum of z coordinate by the bounds
bc = poly.GetBounds()
num_points = poly.GetNumberOfPoints()
p = [0, 0, 0]
small_z = 1000
xof_small_z = 1000
yof_small_z = 1000
small_y = 1000
xof_small_y = 1000
zof_small_y = 1000
for point_index in range(num_points):
poly.GetPoint(point_index, p)
tmp = p[2]
if tmp < small_z:
small_z = tmp
xof_small_z = p[0]
yof_small_z = p[1]
for point_index in range(num_points):
poly.GetPoint(point_index, p)
tmp = p[1]
if tmp < small_y:
small_y = tmp
xof_small_y = p[0]
zof_small_y = p[2]
# in order to put center of mass as
# origin we want to deduct the first one from the rest of the points
com = vtk.vtkCenterOfMass()
com.SetInputData(poly)
com.SetUseScalarsAsWeights(False)
com.Update()
center = com.GetCenter()
return [bc, center,
xof_small_z, yof_small_z, small_z,
xof_small_y, zof_small_y, small_y]
def calculate_center_of_gravity_vtk(self, ):
'''Function to calculate the center of gravity
.. Note::
The VTK Pytnon bindings must be installed to use this function
Examples:
This example assumes that a mesh has been read by bemio and mesh
data is contained in a `PanelMesh` object called `mesh`
>>> mesh.calculate_center_of_gravity_vtk()
'''
if self.VTK_installed is False:
raise VTK_Exception('VTK must be installed to access the calculate_center_of_gravity_vtk function')
com = vtk.vtkCenterOfMass()
com.SetInputData(self.vtp_mesh)
com.Update()
self.center_of_gravity = com.GetCenter()
print 'Calculated center of gravity assuming uniform material density'
def onDoubleClick(self):
nodeID = self.view.currentItem()
if not nodeID:
return
shNode = slicer.mrmlScene.GetSubjectHierarchyNode()
node = shNode.GetItemDataNode(nodeID)
if not isinstance(node, slicer.vtkMRMLModelNode):
return
pd = node.GetPolyData()
center = vtk.vtkCenterOfMass()
center.SetInputData(pd)
center.Update()
centerList = center.GetCenter()
# create markups node, add center as fiducial and jump and center slices
markupsNode = slicer.mrmlScene.AddNewNodeByClass(
'vtkMRMLMarkupsFiducialNode')
markupsNode.GetDisplayNode().SetVisibility(False)
markupsNode.AddFiducialFromArray(np.array(centerList), '')
markupsLogic = slicer.modules.markups.logic()
markupsLogic.JumpSlicesToNthPointInMarkup(markupsNode.GetID(), 0, True)
slicer.mrmlScene.RemoveNode(markupsNode)
def apply_pre_transformation(self, pd):
translation = [0, 0, 0]
if self.config['pre-align']['align_center_of_mass']:
vtk_cm = vtk.vtkCenterOfMass()
vtk_cm.SetInputData(pd)
vtk_cm.SetUseScalarsAsWeights(False)
vtk_cm.Update()
cm = vtk_cm.GetCenter()
translation = [-cm[0], -cm[1], -cm[2]]
t = vtk.vtkTransform()
t.Identity()
rx = self.config['pre-align']['rot_x']
ry = self.config['pre-align']['rot_y']
rz = self.config['pre-align']['rot_z']
s = self.config['pre-align']['scale']
t.Scale(s, s, s)
t.RotateY(ry)
t.RotateX(rx)
t.RotateZ(rz)
t.Translate(translation)
t.Update()
# Transform (assuming only one mesh)
trans = vtk.vtkTransformPolyDataFilter()
trans.SetInputData(pd)
trans.SetTransform(t)
trans.Update()
if self.config['pre-align']['write_pre_aligned']:
name_out = str(self.config.temp_dir / ('pre_transform_mesh.vtk'))
writer = vtk.vtkPolyDataWriter()
writer.SetInputData(trans.GetOutput())
writer.SetFileName(name_out)
writer.Write()
return trans.GetOutput(), t
def RequestData(self, request, inInfo, outInfo):
inp = vtk.vtkDataSet.GetData(inInfo[0])
vec = vtk.vtkDataSet.GetData(inInfo[1])
opt = vtk.vtkPolyData.GetData(outInfo)
origin = np.array(self._normalLine.GetPoints().GetPoint(0))
normal = np.array(self._normalLine.GetPoints().GetPoint(1)) - origin
if np.allclose(normal, [0, 0, 0]):
centerFilter = vtk.vtkCenterOfMass()
centerFilter.SetInputData(inp)
centerFilter.SetUseScalarsAsWeights(False)
centerFilter.Update()
center = centerFilter.GetCenter()
bounds = inp.GetBounds()
origin = [
np.random.triangular(bounds[0], center[0], bounds[1]),
np.random.triangular(bounds[2], center[1], bounds[3]),
np.random.triangular(bounds[4], center[2], bounds[5])
]
normal = sample_spherical(1)
self.SetOrigin(origin)
self.SetNormal(normal)
plane = vtk.vtkPlane()
plane.SetNormal(normal[0], normal[1], normal[2])
plane.SetOrigin(origin[0], origin[1], origin[2])
#create cutter
cutter = vtk.vtkCutter()
cutter.SetCutFunction(plane)
cutter.SetInputData(inp)
cutter.Update()
opt.ShallowCopy(cutter.GetOutput())
return 1
def CenterOfMass(self, scalars_weight=False):
"""
Returns the coordinates for the center of mass of the mesh.
Parameters
----------
scalars_weight : bool, optional
Flag for using the mesh scalars as weights. Defaults to False.
Return
------
center : np.ndarray, float
Coordinates for the center of mass.
"""
comfilter = vtk.vtkCenterOfMass()
comfilter.SetInputData(self)
comfilter.SetUseScalarsAsWeights(scalars_weight)
comfilter.Update()
center = np.array(comfilter.GetCenter())
return center
def Get_Centroids(self,surface_files,filenames):
print ("-"*50)
print ("------ Computing Centroids of Surface Outlets")
Centroids={}
count=0
for surface_file in surface_files:
print ("----Processing %s"%filenames[count])
#Read the Surface File
reader=vtk.vtkXMLPolyDataReader()
reader.SetFileName(surface_file)
reader.Update()
#Get the Centroid
centerOfMassFilter=vtk.vtkCenterOfMass()
centerOfMassFilter.SetInputData(reader.GetOutput())
centerOfMassFilter.SetUseScalarsAsWeights(False)
centerOfMassFilter.Update()
center_=centerOfMassFilter.GetCenter()
Centroids[filenames[count]]=[center_[0],center_[1],center_[2]]
del reader,centerOfMassFilter
count+=1
return Centroids
def run(self, inputVolume, Index):
logging.info('Processing started')
DosiFilmImage = inputVolume
logging.info(DosiFilmImage)
date = datetime.datetime.now()
savepath = u"//s-grp/grp/RADIOPHY/Personnel/Aurélien Corroyer-Dulmont/3dSlicer/Field_Center_vs_Jaw_setting_TOMOTHERAPY_QC_Results/Results_" + str(
date.day) + str(date.month) + str(date.year) + ".txt"
logging.info(savepath)
logging.info(Index)
#### To get background intensity for the thershold value of the bloc
# Create segmentation
segmentationNode = slicer.vtkMRMLSegmentationNode()
slicer.mrmlScene.AddNode(segmentationNode)
segmentationNode.CreateDefaultDisplayNodes() # only needed for display
segmentationNode.SetReferenceImageGeometryParameterFromVolumeNode(
DosiFilmImage)
# Create segment
backgroundSeed = vtk.vtkSphereSource()
backgroundSeed.SetCenter(-40, -30, 0)
backgroundSeed.SetRadius(5)
backgroundSeed.Update()
segmentationNode.AddSegmentFromClosedSurfaceRepresentation(
backgroundSeed.GetOutput(), "Segment A", [1.0, 0.0, 0.0])
mergedLabelmapNode = slicer.vtkMRMLLabelMapVolumeNode()
slicer.mrmlScene.AddNode(mergedLabelmapNode)
sa = vtk.vtkStringArray()
sa.InsertNextValue("Segment A")
slicer.vtkSlicerSegmentationsModuleLogic.ExportSegmentsToLabelmapNode(
segmentationNode, sa, mergedLabelmapNode, DosiFilmImage)
label = su.PullVolumeFromSlicer("LabelMapVolume")
image = su.PullVolumeFromSlicer(DosiFilmImage)
stat_filter_backgroundSeed = sitk.LabelIntensityStatisticsImageFilter()
stat_filter_backgroundSeed.Execute(label, image) #attention à l'ordre
meanBackground = stat_filter_backgroundSeed.GetMean(1)
print(meanBackground)
# Stockage du nom de la machine en utilisant le choix de l'utilisateur dans la class Widget
if Index == 0:
machineName = 'Tomotherapy 1'
else:
machineName = 'Tomotherapy 2'
# Création de la segmentation
segmentationNode = slicer.mrmlScene.AddNewNodeByClass(
"vtkMRMLSegmentationNode")
segmentationNode.CreateDefaultDisplayNodes()
segmentationNode.SetReferenceImageGeometryParameterFromVolumeNode(
DosiFilmImage)
logging.info(segmentationNode)
# Création des segments editors temporaires
segmentEditorWidget = slicer.qMRMLSegmentEditorWidget()
segmentEditorWidget.setMRMLScene(slicer.mrmlScene)
segmentEditorNode = slicer.mrmlScene.AddNewNodeByClass(
"vtkMRMLSegmentEditorNode")
segmentEditorWidget.setMRMLSegmentEditorNode(segmentEditorNode)
segmentEditorWidget.setSegmentationNode(segmentationNode)
segmentEditorWidget.setMasterVolumeNode(DosiFilmImage)
# Création d'un segment après seuillage
addedSegmentID = segmentationNode.GetSegmentation().AddEmptySegment(
"IrradiatedBlocks")
segmentEditorNode.SetSelectedSegmentID(addedSegmentID)
segmentEditorWidget.setActiveEffectByName("Threshold")
effect = segmentEditorWidget.activeEffect()
#effect.setParameter("MinimumThreshold",str(22000))
#effect.setParameter("MaximumThreshold",str(55000))
effect.setParameter("MinimumThreshold", str(meanBackground / 5))
effect.setParameter("MaximumThreshold", str(meanBackground / 1.2))
effect.self().onApply()
# Passage en mode closed surface pour calcul des centres
n = slicer.util.getNode('Segmentation_1')
s = n.GetSegmentation()
ss = s.GetSegment('IrradiatedBlocks')
ss.AddRepresentation('Closed surface', vtk.vtkPolyData())
# Division du segment en plusieurs segments (un par bloc d'irradiation)
segmentEditorWidget.setActiveEffectByName("Islands")
effect = segmentEditorWidget.activeEffect()
effect.setParameter("Operation", str("SPLIT_ISLANDS_TO_SEGMENTS"))
effect.setParameter("MinimumSize", 1000)
effect.self().onApply()
######### Initialisation des variables fixes d'intérêt###########
Segmentation_Name = 'Segmentation_1'
Segment_Name = [
"IrradiatedBlocks", "IrradiatedBlocks -_1", "IrradiatedBlocks -_2",
"IrradiatedBlocks -_3", "IrradiatedBlocks -_4",
"IrradiatedBlocks -_5", "IrradiatedBlocks -_6"
]
ListYaxisCenterOfBlock = [
0, 0, 0, 0, 0, 0, 0
] # initialisation de la liste contenant les valeurs Y centrales des blocs
# Boucle de calcul des centres pour les 7 blocs (segment)
i = 0
while i < len(Segment_Name):
n = slicer.util.getNode(Segmentation_Name)
s = n.GetSegmentation()
ss = s.GetSegment(Segment_Name[i])
pd = ss.GetRepresentation('Closed surface')
com = vtk.vtkCenterOfMass()
com.SetInputData(pd)
com.Update()
com.GetCenter() # A voir mais je pense que cette ligne est inutile
CenterOfBlock = com.GetCenter(
) # CenterOfBlock est alors un tuple avec plusieurs variables (coordonées x,y,z)
YaxisCenterOfBlock = (
CenterOfBlock[1]
) # Sélection de la 2ème valeur du tuple (indice 1) qui est la valeur dans l'axe Y qui est l'unique valeure d'intérêt
YaxisCenterOfBlock = abs(
YaxisCenterOfBlock) # On passe en valeur absolue
ListYaxisCenterOfBlock[i] = YaxisCenterOfBlock
i += 1
logging.info(ListYaxisCenterOfBlock)
######### Calcul de la différence en Y entre les centres des différents blocs###########
MaxYaxisCenter = max(ListYaxisCenterOfBlock)
MinYaxisCenter = min(ListYaxisCenterOfBlock)
DifferenceMaxInPixelYCenters = MaxYaxisCenter - MinYaxisCenter
DifferenceMaxInMmYCenters = float(DifferenceMaxInPixelYCenters)
DifferenceMaxInMmYCenters = DifferenceMaxInMmYCenters * 0.3528 # Pas élégant mais si je ne fais pas ça, il initialise DifferenceMaxInMmYCenters en tuple et pas en variable...
### Enonciation des résultats ###
logging.info("Coordonnee Max en Y : " + str(MaxYaxisCenter))
logging.info("Coordonnee Min en Y : " + str(MinYaxisCenter))
logging.info("Difference maximale entre les blocs (en pixel) : " +
str(DifferenceMaxInPixelYCenters))
logging.info("Difference maximale entre les blocs (en mm) : " +
str(DifferenceMaxInMmYCenters))
######### Création et remplissage fichier text pour stocker les résultats###########
file = open(savepath, 'w')
### encodage du fichier pour écriture incluant les "é" ###
file = codecs.open(savepath, encoding='utf-8')
txt = file.read()
file = codecs.open(savepath, "w", encoding='mbcs')
date = datetime.datetime.now()
file.write(u"Résultats test -Field Center vs Jaw setting-")
file.write("\n\n")
file.write("Machine : " + str(machineName))
file.write("\n\n")
file.write("Date : " + str(date.day) + "/" + str(date.month) + "/" +
str(date.year))
file.write("\n\n")
file.write("\n\n")
i = 0
for i in range(
len(ListYaxisCenterOfBlock)
): # Boucle pour obtenir les coordonées Y des centres des 7 blocs
file.write(u"Coordonnée Y du centre du bloc n°" + str(i + 1) +
": ")
file.write(str(ListYaxisCenterOfBlock[i]))
file.write("\n\n")
file.write("\n\n")
file.write(u"Coordonnée Max en Y : " + str(MaxYaxisCenter))
file.write("\n\n")
file.write(u"Coordonnée Min en Y : " + str(MinYaxisCenter))
file.write("\n\n")
file.write(u"Différence maximale entre les blocs (en pixel) : " +
str(DifferenceMaxInPixelYCenters))
file.write("\n\n")
file.write(u"Différence maximale entre les blocs (en mm) : " +
str(DifferenceMaxInMmYCenters))
######### Calcul de la conformité et mention dans le fichier résultats###########
if 0 <= DifferenceMaxInMmYCenters < 0.5:
Result = "Conforme"
elif DifferenceMaxInMmYCenters > 0.5:
Result = "Hors tolerance"
else:
Result = "Limite" #car si pas < ou > à 0.5 alors = à 0.5
if DifferenceMaxInMmYCenters < 0:
logging.info(
u"Valeur de la différence négative, problème dans l'image ou dans le programme, contactez Aurélien Corroyer-Dulmont tel : 5768"
)
logging.info(Result)
file.write("\n\n")
file.write("\n\n")
file.write(u"Résultat : " + str(Result))
file.close()
logging.info('Processing completed')
logging.info('\n\nResults are in the following file : ' + savepath)
return True
def extractfeatures(self, DICOMImages, image_pos_pat, image_ori_pat, series_path, phases_series, VOI_mesh):
""" Start pixVals for collection pixel values at VOI """
pixVals_margin = []; pixVals = []
Fmargin = {}; voxel_frameS = {}
# necessary to read point coords
VOIPnt = [0,0,0]
ijk = [0,0,0]
pco = [0,0,0]
for i in range(len(DICOMImages)):
# find mapping to Dicom space
[transformed_image, transform_cube] = Display().dicomTransform(DICOMImages[i], image_pos_pat, image_ori_pat)
if (i==0):
# create mask from segmenation
np_VOI_mask = self.createMaskfromMesh(VOI_mesh, transformed_image)
for j in range( VOI_mesh.GetNumberOfPoints() ):
VOI_mesh.GetPoint(j, VOIPnt)
# extract pixID at location VOIPnt
pixId = transformed_image.FindPoint(VOIPnt[0], VOIPnt[1], VOIPnt[2])
im_pt = [0,0,0]
transformed_image.GetPoint(pixId,im_pt)
inorout = transformed_image.ComputeStructuredCoordinates( im_pt, ijk, pco)
if(inorout == 0):
pass
else:
pixValx = transformed_image.GetScalarComponentAsFloat( ijk[0], ijk[1], ijk[2], 0)
pixVals_margin.append(pixValx)
# Now collect pixVals
print "\n Saving %s" % 'Fmargin'+str(i)
Fmargin['Fmargin'+str(i)] = pixVals_margin
pixVals_margin = []
# extract pixID at inside VOIPnt
VOI_scalars = transformed_image.GetPointData().GetScalars()
np_VOI_imagedata = vtk_to_numpy(VOI_scalars)
dims = transformed_image.GetDimensions()
spacing = transformed_image.GetSpacing()
np_VOI_imagedata = np_VOI_imagedata.reshape(dims[2], dims[1], dims[0])
np_VOI_imagedata = np_VOI_imagedata.transpose(2,1,0)
#################### HERE GET INTERNAL PIXELS IT AND MASK IT OUT
VOI_imagedata = np_VOI_imagedata[nonzero(np_VOI_mask)]
for j in range( len(VOI_imagedata) ):
pixValx = VOI_imagedata[j]
pixVals.append(pixValx)
# Now collect pixVals
print "\n Saving %s" % 'F'+str(i)
voxel_frameS['F'+str(i)] = pixVals
pixVals = []
##############################################################
# Initialize features
self.i_var = []; self.alln_F_r_i=[]; self.allmin_F_r_i=[]; self.allmax_F_r_i=[];
self.allmean_F_r_i=[]; self.allvar_F_r_i=[]; self.allskew_F_r_i=[]; self.allkurt_F_r_i=[]
F_r_0 = array(voxel_frameS['F'+str(0)]).astype(float)
n, min_max, meanFr, var_F_r_0, skew, kurt = stats.describe(F_r_0)
self.i_var_max = 0
# Collect to Compute inhomogeneity variance of uptake and other variables
for k in range(1,len(DICOMImages)):
F_r_i = array(voxel_frameS['F'+str(k)]).astype(float)
print "\nF_r_i parameters %s" % str(k)
n_F_r_i, min_max_F_r_i, mean_F_r_i, var_F_r_i, skew_F_r_i, kurt_F_r_i = stats.describe(F_r_i)
print("Number of internal voxels: {0:d}".format(n_F_r_i))
self.alln_F_r_i.append(n_F_r_i)
print("Minimum: {0:8.6f} Maximum: {1:8.6f}".format(min_max_F_r_i[0], min_max_F_r_i[1]))
self.allmin_F_r_i.append(min_max_F_r_i[0])
self.allmax_F_r_i.append(min_max_F_r_i[1])
print("Mean: {0:8.6f}".format(mean_F_r_i))
self.allmean_F_r_i.append(mean_F_r_i)
print("Variance F_r_i: {0:8.6f}".format(var_F_r_i))
self.allvar_F_r_i.append(var_F_r_i)
print("Skew : {0:8.6f}".format(skew_F_r_i))
self.allskew_F_r_i.append(skew_F_r_i)
print("Kurtosis: {0:8.6f}".format(kurt_F_r_i))
self.allkurt_F_r_i.append(kurt_F_r_i)
print("Variance of uptake: {0:8.6f}".format(var_F_r_i/var_F_r_0))
self.i_var.append( var_F_r_i/var_F_r_0 )
# Find max of change in variance of uptake
if( self.i_var[k-1] > self.i_var_max):
self.i_var_max = self.i_var[k-1]
print("\nMax Variance of uptake: {0:8.6f}\n".format( self.i_var_max ))
# Collect to Compute change in variance of uptake
self.ii_var = []
self.ii_var_min = 1000
for k in range(len(DICOMImages)-1):
F_r_i = array(voxel_frameS['F'+str(k)]).astype(float)
F_r_iplus = array(voxel_frameS['F'+str(k+1)]).astype(float)
n, min_max, meanFr, var_F_r_ith, skew, kurt = stats.describe(F_r_i)
n, min_max, meanFr, var_F_r_iplus, skew, kurt = stats.describe(F_r_iplus)
"""change Variance of uptake:"""
self.ii_var.append( var_F_r_ith/var_F_r_iplus )
# Find max of change in variance of uptake
if( var_F_r_ith/var_F_r_iplus < self.ii_var_min):
self.ii_var_min = var_F_r_ith/var_F_r_iplus
print("Min change Variance of uptake: {0:8.6f}\n".format( self.ii_var_min ))
# Extract features for sharpness of lesion margin, compute Margin gradient iii_var
# The gradient is computed using convolution with a 3D sobel filter using scipy.ndimage.filters.sobel
# The function generic_gradient_magnitude calculates a gradient magnitude using the function passed through derivative to calculate first derivatives.
F_rmargin_0 = array(Fmargin['Fmargin'+str(0)]).astype(float)
self.iii_var_max = -1000
iii_Sobelvar = []
# Collect to Compute variance of uptake and other variables
for k in range(1,len(DICOMImages)):
F_rmargin_i = array(Fmargin['Fmargin'+str(k)]).astype(float)
margin_delta = F_rmargin_i-F_rmargin_0
# using first sobel and then prewitt
sobel_grad_margin_delta = generic_gradient_magnitude(margin_delta, sobel)
# compute feature Margin Gradient
n, min_max, mean_sobel_grad_margin, var, skew, kurt = stats.describe(sobel_grad_margin_delta)
n, min_max, mean_F_rmargin_i, var_F_r_ith, skew, kurt = stats.describe(F_rmargin_i)
"""Margin Gradient"""
iii_Sobelvar.append( mean_sobel_grad_margin/mean_F_rmargin_i )
# Find max of Margin Gradient
if( iii_Sobelvar[k-1] > self.iii_var_max):
self.iii_var_max = iii_Sobelvar[k-1]
self.iii_var_max_k = k
print("Max Margin Gradient: {0:8.6f}".format( self.iii_var_max ))
print("k for Max Margin Gradient: {0:8.6f}".format( self.iii_var_max_k ))
# compute iv feature Variance of Margin Gradient
# note: only computed from the subtraction frames of i and 0 where the margin gradient iii_var is maximum.
self.ivVariance = []
F_rmargin_iv = array(Fmargin['Fmargin'+str(self.iii_var_max_k)]).astype(float)
n, min_max, mean_F_rmargin_iv, var_F_r_ith, skew, kurt = stats.describe(F_rmargin_iv)
margin_delta_iv = F_rmargin_iv-F_rmargin_0
# using first sobel and then prewitt
sobel_grad_margin_delta_iv = generic_gradient_magnitude(margin_delta_iv, sobel)
n, min_max, mean_sobel, var_sobel_grad_margin_delta_iv, skew, kurt = stats.describe(sobel_grad_margin_delta_iv)
self.ivVariance = var_sobel_grad_margin_delta_iv/mean_F_rmargin_iv**2
print("Variance of spatial Margin Gradient: {0:8.6f}".format( self.ivVariance ))
# Extract Shape features: pre-requisite is the Volume and the diameter of the lesion
####################################
# Measure VOI
###################################
VOI_massProperty = vtk.vtkMassProperties()
VOI_massProperty.SetInputData(VOI_mesh)
VOI_massProperty.Update()
# get VOI volume
# VTK is unitless. The units you get out are the units you put in.
# If your input polydata has points defined in terms of millimetres, then
# the volume will be in cubic millimetres.
VOI_vol = VOI_massProperty.GetVolume() # mm3
VOI_surface = VOI_massProperty.GetSurfaceArea() # mm2
# just print the results
print "\nVolume lesion = ", VOI_vol
print "Surface lesion = ", VOI_surface
# Calculate the effective diameter of the surface D=2(sqrt3(3V/(4pi)))
diam_root = (3*VOI_vol)/(4*pi)
self.VOI_efect_diameter = 2*pow(diam_root,1.0/3)
print "VOI_efect_diameter = ", self.VOI_efect_diameter
centerOfMassFilter = vtk.vtkCenterOfMass()
centerOfMassFilter.SetInputData( VOI_mesh )
centerOfMassFilter.SetUseScalarsAsWeights(False)
centerOfMassFilter.Update()
# centroid of lesion
self.lesion_centroid = [0,0,0]
self.lesion_centroid = centerOfMassFilter.GetCenter()
print "lesion_centroid = ", self.lesion_centroid
# create a sphere to compute the volume of lesion within a sphere of effective diameter
sphere_effectD = vtk.vtkSphereSource()
sphere_effectD.SetRadius(self.VOI_efect_diameter/2) #VOI_diameter/2
sphere_effectD.SetCenter(self.lesion_centroid)
sphere_effectD.Update()
# compute volume of lesion within a sphere of effective diameter
sphereVOI_massProperty = vtk.vtkMassProperties()
sphereVOI_massProperty.SetInputData(sphere_effectD.GetOutput())
sphereVOI_massProperty.Update()
sphereVOI_vol = sphereVOI_massProperty.GetVolume() # mm3
# just print the results
print "Volume sphereVOI = ", sphereVOI_vol
# Compute Shape of lesion in 3D
# Circularity
epsilon = 0.001
self.circularity = sphereVOI_vol/(VOI_vol+epsilon)
print("\nCircularity: {0:8.6f}".format( self.circularity ))
self.irregularity = 1 - pi*(self.VOI_efect_diameter/VOI_surface)
print("Irregularity: {0:8.6f}".format( self.irregularity ))
####################################
# Radial gradient analysis ref[9] white paper
###################################
# Radial gradient analysis is based on examination of the angles between voxel-value gradients
# and lines intersecting a single point near the center of the suspect lesion, lines in radial directions.
# Radial gradient values are given by the dot product of the gradient direction and the radial direction.
RGH_mean = []; self.max_RGH_mean = 0; self.max_RGH_mean_k = 0; RGH_var = []; self.max_RGH_var = 0; self.max_RGH_var_k = 0;
H_norm_p = []
# do subtraction of timepost-pre
####################
for i in range(1,len(DICOMImages)):
subtractedImage = Display().subImage(DICOMImages, i)
[transformed_image, transform_cube] = Display().dicomTransform(subtractedImage, image_pos_pat, image_ori_pat)
for j in range( VOI_mesh.GetNumberOfPoints() ):
VOI_mesh.GetPoint(j, VOIPnt)
r = array(VOIPnt)
rc = array(self.lesion_centroid)
norm_rdir = (r-rc)/linalg.norm(r-rc)
# Find point for gradient vectors at the margin point
pixId = transformed_image.FindPoint(VOIPnt[0], VOIPnt[1], VOIPnt[2])
sub_pt = [0,0,0]
transformed_image.GetPoint(pixId, sub_pt)
ijk = [0,0,0]
pco = [0,0,0]
grad_pt = [0,0,0];
inorout = transformed_image.ComputeStructuredCoordinates( sub_pt, ijk, pco)
if(inorout == 0):
print "point outside data"
else:
transformed_image.GetPointGradient( ijk[0], ijk[1], ijk[2], transformed_image.GetPointData().GetScalars(), grad_pt)
#############
# Compute vector in the direction gradient at margin point
grad_marginpt = array([grad_pt])
norm_grad_marginpt = grad_marginpt/linalg.norm(grad_marginpt)
# Compute dot product (unit vector for dot product)
p_dot = dot(norm_grad_marginpt, norm_rdir)
norm_p_dot = np.abs(p_dot)[0] #linalg.norm(p_dot)
H_norm_p.append(norm_p_dot)
# The histogram of radial gradient values quantifying the frequency of occurrence of the dot products in a given region of interest
# radial gradient histogram. The hist() function now has a lot more options
# first create a single histogram
# the histogram of the data with histtype='step'
# plt.figure()
# nsamples, bins, patches = plt.hist(array(H_norm_p), 50, normed=1, histtype='bar',facecolor='blue', alpha=0.75)
# n, min_max, mean_bins, var_bins, skew, kurt = stats.describe(nsamples)
mean_bins = np.mean(H_norm_p)
var_bins = np.var(H_norm_p)
print("\n mean RGB: {0:8.6f}".format( mean_bins ))
print("variance RGB: {0:8.6f}".format( var_bins ))
# Append data
RGH_mean.append( mean_bins )
RGH_var.append( var_bins )
# Find max of RGH Gradient
if( RGH_mean[i-1] > self.max_RGH_mean):
self.max_RGH_mean = RGH_mean[i-1]
self.max_RGH_mean_k = i
if( RGH_var[i-1] > self.max_RGH_var):
self.max_RGH_var = RGH_var[i-1]
self.max_RGH_var_k = i
# add a line showing the expected distribution
# create a histogram by providing the bin edges (unequally spaced)
plt.xlabel('normalized dot product |R.G|')
plt.ylabel('Probability')
plt.title('radial gradient histogram')
plt.grid(True)
################# Jacob's lesion margin sharpness
#initializations
VOI_outlinept_normal = [0,0,0]; VOI_outlinept = [0,0,0]; inpt = [0,0,0]; outpt = [0,0,0]
im_pts = [0,0,0]; ijk_in = [0,0,0]; ijk_out = [0,0,0]; pco = [0,0,0]; SIout_pixVal=[]; lastSIout_pixVal=[]
# get model_point_normals
VOI_point_normals = vtk.vtkPolyDataNormals()
VOI_point_normals.SetInputData( VOI_mesh )
VOI_point_normals.SetComputePointNormals(1)
VOI_point_normals.SetComputeCellNormals(0)
VOI_point_normals.SplittingOff()
VOI_point_normals.FlipNormalsOff()
VOI_point_normals.ConsistencyOn()
VOI_point_normals.Update()
# Retrieve model normals
VOI_normalsRetrieved = VOI_point_normals.GetOutput().GetPointData().GetNormals()
VOI_n = VOI_normalsRetrieved.GetNumberOfTuples()
# obtain vols of interest
[transf_pre_dicomReader, transform_cube] = Display().dicomTransform(DICOMImages[0], image_pos_pat, image_ori_pat)
[transf_last_dicomReader, transform_cube] = Display().dicomTransform(DICOMImages[len(DICOMImages)-1], image_pos_pat, image_ori_pat)
num_margin = []
den_margin = []
for i in range(1,len(DICOMImages)):
#initializations
SIout_pixVal=[]
lastSIout_pixVal=[]
subtractedImage = Display().subImage(DICOMImages, i)
[transf_sub_pre_dicomReader, transform_cube] = Display().dicomTransform(subtractedImage, image_pos_pat, image_ori_pat)
for k in range( VOI_n ):
VOI_outlinept_normal = VOI_normalsRetrieved.GetTuple3(k)
VOI_mesh.GetPoint(k, VOI_outlinept)
# "d for radial lenght: %f" % d
d = sqrt(spacing[0]**2 + spacing[1]**2 + spacing[2]**2)
inpt[0] = VOI_outlinept[0] - VOI_outlinept_normal[0]*d
inpt[1] = VOI_outlinept[1] - VOI_outlinept_normal[1]*d
inpt[2] = VOI_outlinept[2] - VOI_outlinept_normal[2]*d
outpt[0] = VOI_outlinept[0] + VOI_outlinept_normal[0]*d
outpt[1] = VOI_outlinept[1] + VOI_outlinept_normal[1]*d
outpt[2] = VOI_outlinept[2] + VOI_outlinept_normal[2]*d
# get pre-contrast SIin to normalized RSIgroup [See equation 1] from paper
prepixin = transf_pre_dicomReader.FindPoint(inpt[0], inpt[1], inpt[2])
transf_pre_dicomReader.GetPoint(prepixin,im_pts)
transf_pre_dicomReader.ComputeStructuredCoordinates( im_pts, ijk_in, pco)
#print ijk_in
# get pre-contrast SIout in 6-c-neighbordhood to normalized RSIgroup [See equation 1] from paper
prepixout = transf_pre_dicomReader.FindPoint(outpt[0], outpt[1], outpt[2])
transf_pre_dicomReader.GetPoint(prepixout,im_pts)
transf_pre_dicomReader.ComputeStructuredCoordinates( im_pts, ijk_out, pco)
#print ijk_out
# get t-post SIin
SIin_pixVal = transf_sub_pre_dicomReader.GetScalarComponentAsFloat( ijk_in[0], ijk_in[1], ijk_in[2], 0 )
preSIin_pixVal = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_in[0], ijk_in[1], ijk_in[2], 0 )+epsilon
RSIin = SIin_pixVal/preSIin_pixVal
####
# get t-post SIout 6-c-neighbordhood
#cn1
SIout = transf_sub_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0]+1, ijk_out[1], ijk_out[2], 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0]+1, ijk_out[1], ijk_out[2], 0 )+epsilon
SIout_pixVal.append(float(SIout/preSIout))
#cn2
SIout = transf_sub_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0]-1, ijk_out[1], ijk_out[2], 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0]-1, ijk_out[1], ijk_out[2], 0 )+epsilon
SIout_pixVal.append(float(SIout/preSIout))
#cn3
SIout = transf_sub_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]+1, ijk_out[2], 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]+1, ijk_out[2], 0 )+epsilon
SIout_pixVal.append(float(SIout/preSIout))
#cn4
SIout = transf_sub_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]-1, ijk_out[2], 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]-1, ijk_out[2], 0 )+epsilon
SIout_pixVal.append(float(SIout/preSIout))
#cn5
SIout = transf_sub_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1], ijk_out[2]+1, 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1], ijk_out[2]+1, 0 )+epsilon
SIout_pixVal.append(float(SIout/preSIout))
#cn6
SIout = transf_sub_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]-1, ijk_out[2]-1, 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]-1, ijk_out[2]-1, 0 )+epsilon
SIout_pixVal.append(float(SIout/preSIout))
RSIout = mean( SIout_pixVal )
###
# get last-post SIout 6-c-neighbordhood
#cn1
SIout = transf_last_dicomReader.GetScalarComponentAsFloat( ijk_out[0]+1, ijk_out[1], ijk_out[2], 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0]+1, ijk_out[1], ijk_out[2], 0 )+epsilon
lastSIout_pixVal.append(float(SIout/preSIout))
#cn2
SIout = transf_last_dicomReader.GetScalarComponentAsFloat( ijk_out[0]-1, ijk_out[1], ijk_out[2], 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0]-1, ijk_out[1], ijk_out[2], 0 )+epsilon
lastSIout_pixVal.append(float(SIout/preSIout))
#cn3
SIout = transf_last_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]+1, ijk_out[2], 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]+1, ijk_out[2], 0 )+epsilon
lastSIout_pixVal.append(float(SIout/preSIout))
#cn4
SIout = transf_last_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]-1, ijk_out[2], 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]-1, ijk_out[2], 0 )+epsilon
lastSIout_pixVal.append(float(SIout/preSIout))
#cn5
SIout = transf_last_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1], ijk_out[2]+1, 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1], ijk_out[2]+1, 0 )+epsilon
lastSIout_pixVal.append(float(SIout/preSIout))
#cn6
SIout = transf_last_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]-1, ijk_out[2]-1, 0 )
preSIout = transf_pre_dicomReader.GetScalarComponentAsFloat( ijk_out[0], ijk_out[1]-1, ijk_out[2]-1, 0 )+epsilon
lastSIout_pixVal.append(float(SIout/preSIout))
# calculate
RSIoutf = mean( lastSIout_pixVal )
### compute feature
num_margin.append( RSIin-RSIout )
den_margin.append( RSIin-RSIoutf )
#print num_margin
#print den_margin
SIout_pixVal=[]
lastSIout_pixVal=[]
self.edge_sharp_mean = mean(array(num_margin).astype(float)) / mean(array(den_margin).astype(float))
self.edge_sharp_std = std(array(num_margin).astype(float)) / std(array(den_margin).astype(float))
print "\n edge_sharp_mean: "
print self.edge_sharp_mean
print "\n edge_sharp_std: "
print self.edge_sharp_std
##################################################
# orgamize into dataframe
self.morphologyFeatures = DataFrame( data=array([[ mean(self.allmin_F_r_i), mean(self.allmax_F_r_i),mean(self.allmean_F_r_i), mean(self.allvar_F_r_i), mean(self.allskew_F_r_i), mean(self.allkurt_F_r_i),
self.i_var_max, self.ii_var_min, self.iii_var_max, self.iii_var_max_k, self.ivVariance, self.circularity, self.irregularity, self.edge_sharp_mean, self.edge_sharp_std, self.max_RGH_mean, self.max_RGH_mean_k, self.max_RGH_var, self.max_RGH_var_k ]]),
columns=['min_F_r_i', 'max_F_r_i', 'mean_F_r_i', 'var_F_r_i', 'skew_F_r_i', 'kurt_F_r_i',
'iMax_Variance_uptake', 'iiMin_change_Variance_uptake', 'iiiMax_Margin_Gradient', 'k_Max_Margin_Grad', 'ivVariance', 'circularity', 'irregularity', 'edge_sharp_mean', 'edge_sharp_std', 'max_RGH_mean', 'max_RGH_mean_k', 'max_RGH_var', 'max_RGH_var_k'])
return self.morphologyFeatures
def addSegment(self, lesion3D, color, interact):
'''Add segmentation to current display'''
# Set the planes based on seg bounds
self.lesion_bounds = lesion3D.GetBounds()
print "\n Mesh DICOM bounds: "
print "xmin, xmax= [%d, %d]" % (self.lesion_bounds[0], self.lesion_bounds[1])
print "yin, ymax= [%d, %d]" % (self.lesion_bounds[2], self.lesion_bounds[3])
print "zmin, zmax= [%d, %d]" % (self.lesion_bounds[4], self.lesion_bounds[5])
### GEt semgnetation information
self.no_pts_segm = lesion3D.GetNumberOfPoints()
print "no pts %d" % self.no_pts_segm
# get VOI volume
VOI_massProperty = vtk.vtkMassProperties()
VOI_massProperty.SetInput(lesion3D)
VOI_massProperty.Update()
# VTK is unitless. The units you get out are the units you put in.
# If your input polydata has points defined in terms of millimetres, then
# the volume will be in cubic millimetres.
self.VOI_vol = VOI_massProperty.GetVolume() # mm3
self.VOI_surface = VOI_massProperty.GetSurfaceArea() # mm2
# just print the results
print "\nVolume lesion = ", self.VOI_vol
print "Surface lesion = ", self.VOI_surface
# Calculate the effective diameter of the surface D=2(sqrt3(3V/(4pi)))
diam_root = (3*self.VOI_vol)/(4*pi)
self.VOI_efect_diameter = 2*pow(diam_root,1.0/3)
print "VOI_efect_diameter = ", self.VOI_efect_diameter
centerOfMassFilter = vtk.vtkCenterOfMass()
centerOfMassFilter.SetInput( lesion3D )
centerOfMassFilter.SetUseScalarsAsWeights(False)
centerOfMassFilter.Update()
# centroid of lesion
self.lesion_centroid = [0,0,0]
self.lesion_centroid = centerOfMassFilter.GetCenter()
print "lesion_centroid = ", self.lesion_centroid
self.lesioncentroidijk()
# Add ICPinit_mesh.vtk to the render
self.mapper_mesh = vtk.vtkPolyDataMapper()
self.mapper_mesh.SetInput( lesion3D )
self.mapper_mesh.ScalarVisibilityOff()
self.actor_mesh = vtk.vtkActor()
self.actor_mesh.SetMapper(self.mapper_mesh)
self.actor_mesh.GetProperty().SetColor(color) #R,G,B
self.actor_mesh.GetProperty().SetOpacity(0.3)
self.actor_mesh.GetProperty().SetPointSize(5.0)
self.actor_mesh.GetProperty().SetRepresentationToWireframe()
self.xImagePlaneWidget.SetSliceIndex(0)
self.yImagePlaneWidget.SetSliceIndex(0)
self.zImagePlaneWidget.SetSliceIndex( 0 )
self.renderer1.AddActor(self.actor_mesh)
# Initizalize
self.renderer1.Modified()
self.renWin1.Render()
self.renderer1.Render()
if(interact==True):
self.iren1.Start()
return
def get_center(_mesh):
centerofmass = vtk.vtkCenterOfMass()
centerofmass.SetInputData(_mesh.GetOutput())
centerofmass.Update()
return np.array(centerofmass.GetCenter())
MARCHING_CUBES_THRESHOLD = 0.01 #************* GET CENTER OF MASS OF WHOLE STRUCTURE SO WE CAN TRANSLATE PARTS #Run marching cubes on the whole input image fltMarching_whole = vtk.vtkMarchingCubes() #***** Discrete version instead? fltMarching_whole.SetInputData(imageData) fltMarching_whole.ComputeScalarsOff() fltMarching_whole.ComputeGradientsOff() fltMarching_whole.ComputeNormalsOn() fltMarching_whole.SetNumberOfContours(1) fltMarching_whole.SetValue(0, MARCHING_CUBES_THRESHOLD) fltMarching_whole.Update() centerFilter = vtk.vtkCenterOfMass() centerFilter.SetInputConnection(fltMarching_whole.GetOutputPort()) centerFilter.SetUseScalarsAsWeights(False) centerFilter.Update() center = centerFilter.GetCenter() transform = vtk.vtkTransform() transform.PostMultiply() transform.Translate(-center[0], -center[1], -center[2]) transform.RotateWXYZ(args.x_rot, 1, 0, 0) transform.RotateWXYZ(args.y_rot, 0, 1, 0) transform.RotateWXYZ(args.z_rot, 0, 0, 1) #************** GET RANGE OF LABELS imageScalars = imageData.GetPointData().GetScalars() iMin, iMax = imageScalars.GetValueRange() assert iMin == 0
def Initialize(self):
self.renderer = vtk.vtkRenderer()
self.vtkWidget.GetRenderWindow().AddRenderer(self.renderer)
self.interactor = self.vtkWidget.GetRenderWindow().GetInteractor()
self.centerOfPolyData = vtk.vtkCenterOfMass()
self.markedTissues = []
self.sister1 = None # set these two as sisters
self.sister2 = None
self.calToMarkTissues()
self.resetActors()
self.fillListWidget()
self.addActorsToRender()
self.calCenter()
self.setupCamera()
self.zoomExtents()
self.myInteractorStyle = interact.MyInteractorStyle()
self.interactor.SetInteractorStyle(self.myInteractorStyle)
if (not self.isTraining):
self.createCSVfile()
def kayboardPressedActor(obj, ev):
self.logFile.recordPress("Keyboard", obj.GetKeySym(),
self.camera.GetPosition(),
self.camera.GetFocalPoint(),
self.camera.GetDistance())
self.interactor.AddObserver('KeyPressEvent', kayboardPressedActor,
-1.0)
def wheelForward(obj, ev):
self.logFile.record3DInteraction("ZoomIn",
self.camera.GetPosition(),
self.camera.GetFocalPoint(),
self.camera.GetDistance())
def wheelBackward(obj, ev):
self.logFile.record3DInteraction("ZoomOut",
self.camera.GetPosition(),
self.camera.GetFocalPoint(),
self.camera.GetDistance())
self.interactor.AddObserver('MouseWheelForwardEvent', wheelForward,
-1.0)
self.interactor.AddObserver('MouseWheelBackwardEvent',
wheelBackward, -1.0)
self.lastSingleClicked = None
self.lastDoubleClicked = None
self.numberOfClicks = 0
self.prePosition = [0, 0]
self.resetPixelDistance = 0
def leftClickedActorHighlight(obj, ev):
self.numberOfClicks += 1
clickPos = obj.GetEventPosition()
xdist = clickPos[0] - self.prePosition[0]
ydist = clickPos[1] - self.prePosition[1]
self.prePosition = clickPos
moveDistance = int(math.sqrt(xdist * xdist + ydist * ydist))
picker = vtk.vtkPropPicker()
picker.Pick(clickPos[0], clickPos[1], 0,
obj.FindPokedRenderer(clickPos[0], clickPos[1]))
NewPickedActor = picker.GetActor()
if (moveDistance > self.resetPixelDistance):
self.numberOfClicks = 1
if (NewPickedActor and NewPickedActor in self.modelActors):
index = self.modelActors.index(NewPickedActor)
if (index != self.lastDoubleClicked):
if (self.lastSingleClicked != None
and self.lastSingleClicked != index
and self.lastSingleClicked
not in self.markedTissues):
self.modelActors[
self.lastSingleClicked].GetProperty().DeepCopy(
self.originalProperty[
self.lastSingleClicked])
# if in focus view, highlight item in the neighbor list. or highlight in tissue list
if (self.lastDoubleClicked != None
and self.lastSingleClicked != index
and self.lastDoubleClicked
not in self.markedTissues):
self.highlightList(self.neighborList,
self.findIndexOfOri(index))
if (self.findIndexOfOri(index) in self.neighbors):
self.formNeighborText(
index,
self.neighbors.index(
self.findIndexOfOri(index)))
interact.highLightNeighbor(
self.modelActors[index].GetProperty())
if (not self.isTraining):
self.logFile.updateSister(
2, self.findIndexOfOri(index),
self.neighbors.index(
self.findIndexOfOri(index)),
fixedSurface.outsideOrInside(
self.findIndexOfOri(index)))
else:
self.highlightList(self.tissueList, index)
interact.highLightTissue(
self.modelActors[index].GetProperty())
self.lastSingleClicked = index
if (not self.isTraining):
self.logFile.recordClick("Click", "MainView",
self.findIndexOfOri(index),
self.camera.GetPosition(),
self.camera.GetFocalPoint(),
self.camera.GetDistance())
if (self.numberOfClicks == 2):
if (NewPickedActor and NewPickedActor in self.modelActors):
index = self.modelActors.index(NewPickedActor)
if (self.lastDoubleClicked != None
and index != self.lastDoubleClicked):
self.numberOfClicks = 0
return
if (self.textOn == True
and index == self.lastDoubleClicked):
self.renderer.RemoveActor2D(self.neighborTextActor)
self.textOn = False
self.highlightList(self.tissueList, index)
self.showNeighbors(self.findIndexOfOri(index))
if (self.lastSingleClicked != None and
self.lastSingleClicked not in self.markedTissues):
self.modelActors[
self.lastSingleClicked].GetProperty().DeepCopy(
self.originalProperty[self.lastSingleClicked])
self.lastSingleClicked = None
# if (self.lastDoubleClicked != None and self.lastDoubleClicked not in self.markedTissues):
# self.modelActors[self.lastDoubleClicked].GetProperty().DeepCopy(self.originalProperty[self.lastDoubleClicked])
if (self.lastDoubleClicked == None):
for actor in self.renderer.GetActors():
self.renderer.RemoveActor(actor)
self.renderer.AddActor(self.modelActors[index])
interact.highLightTissue(
self.modelActors[index].GetProperty())
neighbors = self.neighborsInOrderOfCells[
self.findIndexOfOri(index)].copy()
for neighbor in neighbors:
if (self.findIndexOfList(neighbor)
not in self.markedTissues):
self.renderer.AddActor(self.modelActors[
self.findIndexOfList(neighbor)])
if (not self.isTraining):
self.logFile.updateSister(
1, self.findIndexOfOri(index), len(neighbors),
fixedSurface.outsideOrInside(
self.findIndexOfOri(index)))
self.camera.SetFocalPoint(
self.modelActors[index].GetCenter())
# interact.highLightTissue(self.modelActors[index].GetProperty())
self.lastDoubleClicked = index
elif (self.lastDoubleClicked == index):
if (not self.isTraining):
self.logFile.updateSister(1, "-", "-", "-")
self.logFile.updateSister(2, "-", "-", "-")
for actor in self.modelActors:
if (self.modelActors.index(actor)
not in self.markedTissues and actor
not in self.renderer.GetActors()):
self.renderer.AddActor(actor)
self.modelActors[index].GetProperty().DeepCopy(
self.originalProperty[self.lastDoubleClicked])
self.lastDoubleClicked = None
self.lastSingleClicked = None
self.neighborList.clear()
self.vtkWidget.GetRenderWindow().Render()
if (not self.isTraining):
self.logFile.recordClick("DoubleClick", "MainView",
self.findIndexOfOri(index),
self.camera.GetPosition(),
self.camera.GetFocalPoint(),
self.camera.GetDistance())
self.numberOfClicks = 0
self.interactor.AddObserver('LeftButtonPressEvent',
leftClickedActorHighlight, -1.0)
self.tissueList.itemSelectionChanged.connect(self.listPressed)
self.tissueList.itemDoubleClicked.connect(self.listDoubleClicked)
self.neighborList.itemSelectionChanged.connect(
self.neighborListClicked)
self.setAsSisterButton.clicked.connect(self.clickSetSister)
self.interactor.Initialize()
self.interactor.Start()
def addSegment(self, lesion3D, color, interact=False):
'''Add segmentation to current display'''
# Set the planes based on seg bounds
self.lesion_bounds = lesion3D.GetBounds()
print "\n Mesh DICOM bounds: "
print "xmin, xmax= [%d, %d]" % (self.lesion_bounds[0], self.lesion_bounds[1])
print "yin, ymax= [%d, %d]" % (self.lesion_bounds[2], self.lesion_bounds[3])
print "zmin, zmax= [%d, %d]" % (self.lesion_bounds[4], self.lesion_bounds[5])
### GEt semgnetation information
self.no_pts_segm = lesion3D.GetNumberOfPoints()
print "no pts %d" % self.no_pts_segm
# get VOI volume
VOI_massProperty = vtk.vtkMassProperties()
VOI_massProperty.SetInputData(lesion3D)
VOI_massProperty.Update()
# VTK is unitless. The units you get out are the units you put in.
# If your input polydata has points defined in terms of millimetres, then
# the volume will be in cubic millimetres.
self.VOI_vol = VOI_massProperty.GetVolume() # mm3
self.VOI_surface = VOI_massProperty.GetSurfaceArea() # mm2
# just print the results
print "\nVolume lesion = ", self.VOI_vol
print "Surface lesion = ", self.VOI_surface
# Calculate the effective diameter of the surface D=2(sqrt3(3V/(4pi)))
diam_root = (3*self.VOI_vol)/(4*pi)
self.VOI_efect_diameter = 2*pow(diam_root,1.0/3)
print "VOI_efect_diameter = ", self.VOI_efect_diameter
centerOfMassFilter = vtk.vtkCenterOfMass()
centerOfMassFilter.SetInputData( lesion3D )
centerOfMassFilter.SetUseScalarsAsWeights(False)
centerOfMassFilter.Update()
# centroid of lesion
self.lesion_centroid = [0,0,0]
self.lesion_centroid = centerOfMassFilter.GetCenter()
print "lesion_centroid = ", self.lesion_centroid
# Add ICPinit_mesh.vtk to the render
self.mapper_mesh = vtk.vtkPolyDataMapper()
self.mapper_mesh.SetInputData( lesion3D )
self.mapper_mesh.ScalarVisibilityOff()
self.actor_mesh = vtk.vtkActor()
self.actor_mesh.SetMapper(self.mapper_mesh)
self.actor_mesh.GetProperty().SetColor(color) #R,G,B
self.actor_mesh.GetProperty().SetOpacity(0.3)
self.actor_mesh.GetProperty().SetPointSize(5.0)
self.actor_mesh.GetProperty().SetRepresentationToWireframe()
self.xImagePlaneWidget.SetSliceIndex(0)
self.yImagePlaneWidget.SetSliceIndex(0)
self.zImagePlaneWidget.SetSliceIndex( 0 )
self.renderer1.AddActor(self.actor_mesh)
# Initizalize
self.renderer1.Modified()
self.renWin1.Render()
self.renderer1.Render()
if(interact==True):
self.iren1.Start()
return
def getCenterOfMass(self,contour):
comFilter = vtk.vtkCenterOfMass()
comFilter.SetInputData(contour)
comFilter.SetUseScalarsAsWeights(False)
comFilter.Update()
return comFilter.GetCenter()