lassoan

# Load dry bone CT of skull into the scene and run this script to automatically segment endocranium

masterVolumeNode = slicer.mrmlScene.GetFirstNodeByClass("vtkMRMLScalarVolumeNode")
smoothingKernelSizeMm = 3.0  # this is used for closing small holes in the se

# Compute bone threshold value automatically
import vtkITK
thresholdCalculator = vtkITK.vtkITKImageThresholdCalculator()
thresholdCalculator.SetInputData(masterVolumeNode.GetImageData())
thresholdCalculator.SetMethodToOtsu()

lassoan

# Load/generate input data
################################################

# Load master volume
import SampleData
sampleDataLogic = SampleData.SampleDataLogic()
masterVolumeNode = sampleDataLogic.downloadMRBrainTumor1()

# Define boundary points
import numpy as np

lassoan

# Get a dental CT scan
import SampleData
volumeNode = SampleData.SampleDataLogic().downloadDentalSurgery()[1]

# Define curve
curveNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLMarkupsCurveNode')
curveNode.CreateDefaultDisplayNodes()
curveNode.GetCurveGenerator().SetNumberOfPointsPerInterpolatingSegment(25) # add more curve points between control points than the default 10
curveNode.AddControlPoint(vtk.vtkVector3d(-45.85526315789473,	-104.59210526315789,	74.67105263157896))
curveNode.AddControlPoint(vtk.vtkVector3d(-50.9078947368421,	-90.06578947368418,	66.4605263157895))

lassoan

import os
import unittest
import vtk, qt, ctk, slicer
from slicer.ScriptedLoadableModule import *
from array import array
import logging
import vtk.util.numpy_support
import numpy as np

#

lassoan

volumesDir = r"c:\Users\andra\OneDrive\Projects\SlicerTesting4\20190523-AutoWWWL\volumes"
screenshotsDir = r"c:\Users\andra\OneDrive\Projects\SlicerTesting4\20190523-AutoWWWL\screenshots"

methods = [
    ["baseline", autoContrastSlicerDefault],
    ["hist-0.1-99.9", lambda fn: autoContrastVtkImageHistogramStatisticsDefault(fn, 0.1, 99.9, 0.00, 0.0)], # = itksnap
    ["hist-1.0-99.9", lambda fn: autoContrastVtkImageHistogramStatisticsDefault(fn, 1.0, 99.9, 0.10, 0.0)],
    ["hist-1.0-99.0-x0.10", lambda fn: autoContrastVtkImageHistogramStatisticsDefault(fn, 1.0, 99.0, 0.10, 0.10)],
    ["hist-1.0-99.0-x0.20", lambda fn: autoContrastVtkImageHistogramStatisticsDefault(fn, 1.0, 99.0, 0.10, 0.20)],
    ]

lassoan

# Download a sample data set (chest CT)
import SampleData
masterVolumeNode = SampleData.SampleDataLogic().downloadCTChest()

# Create segmentation
segmentationNode = slicer.mrmlScene.AddNewNodeByClass("vtkMRMLSegmentationNode")
segmentationNode.CreateDefaultDisplayNodes() # only needed for display
segmentationNode.SetReferenceImageGeometryParameterFromVolumeNode(masterVolumeNode)

# Create temporary segment editor to get access to effects

lassoan

def showSimpleUserInterface(simpleView):

    # Do not store these display settings permanently
    settings = qt.QSettings()
    settings.setValue('MainWindow/RestoreGeometry', not simpleView)

    for toolbar in slicer.util.mainWindow().findChildren('QToolBar'):
        toolbar.setVisible(not simpleView)

    modulePanelDockWidget = slicer.util.mainWindow().findChildren('QDockWidget','PanelDockWidget')[0]

lassoan

# The module is now moved to SlicerSandbox extension:
#
#   https://github.com/PerkLab/SlicerSandbox/tree/master/SegmentCrossSectionArea
#

lassoan

# Important: the input volume must have isotropic spacing.
# If surface is thick, use Extract skeleton module with Skeleton type = 2D, Do not prune branches = enabled.
# Increase radius parameter to fill more holes.
# Increase dimension to preserve more details.

inputLabelmap = getNode('Input labelmap')

ici = vtk.vtkImageChangeInformation()
ici.SetInputData(inputLabelmap.GetImageData())
ici.SetOutputSpacing(inputLabelmap.GetSpacing())

lassoan

# Generate input data
################################################

import SampleData
import numpy as np

# Load master volume
sampleDataLogic = SampleData.SampleDataLogic()
masterVolumeNode = sampleDataLogic.downloadMRBrainTumor1()