This example shows how to estimate fat, muscle, and bone volume in a CT image by simple thresholding.

SegmentByThresholding.py

# 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
segmentEditorWidget = slicer.qMRMLSegmentEditorWidget()
segmentEditorWidget.setMRMLScene(slicer.mrmlScene)
segmentEditorNode = slicer.mrmlScene.AddNewNodeByClass("vtkMRMLSegmentEditorNode")
segmentEditorWidget.setMRMLSegmentEditorNode(segmentEditorNode)
segmentEditorWidget.setSegmentationNode(segmentationNode)
segmentEditorWidget.setMasterVolumeNode(masterVolumeNode)

# Create segments by thresholding
segmentsFromHounsfieldUnits = [
    ["fat", -200, -50],
    ["muscle", 25, 70],
    ["bone", 130, 3000] ]
for segmentName, thresholdMin, thresholdMax in segmentsFromHounsfieldUnits:
    # Create segment
    addedSegmentID = segmentationNode.GetSegmentation().AddEmptySegment(segmentName)
    segmentEditorNode.SetSelectedSegmentID(addedSegmentID)
    # Fill by thresholding
    segmentEditorWidget.setActiveEffectByName("Threshold")
    effect = segmentEditorWidget.activeEffect()
    effect.setParameter("MinimumThreshold",str(thresholdMin))
    effect.setParameter("MaximumThreshold",str(thresholdMax))
    effect.self().onApply()

# Delete temporary segment editor
segmentEditorWidget = None
slicer.mrmlScene.RemoveNode(segmentEditorNode)

# Compute segment volumes
resultsTableNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLTableNode')
import SegmentStatistics
segStatLogic = SegmentStatistics.SegmentStatisticsLogic()
segStatLogic.getParameterNode().SetParameter("Segmentation", segmentationNode.GetID())
segStatLogic.getParameterNode().SetParameter("ScalarVolume", masterVolumeNode.GetID())
segStatLogic.getParameterNode().SetParameter("LabelmapSegmentStatisticsPlugin.enabled","False")
segStatLogic.getParameterNode().SetParameter("ScalarVolumeSegmentStatisticsPlugin.voxel_count.enabled","False")
segStatLogic.getParameterNode().SetParameter("ScalarVolumeSegmentStatisticsPlugin.volume_mm3.enabled","False")
segStatLogic.computeStatistics()
segStatLogic.exportToTable(resultsTableNode)
segStatLogic.showTable(resultsTableNode)

# Export segmentation to a labelmap
labelmapVolumeNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLLabelMapVolumeNode')
slicer.modules.segmentations.logic().ExportVisibleSegmentsToLabelmapNode(segmentationNode, labelmapVolumeNode, masterVolumeNode)
slicer.util.saveNode(labelmapVolumeNode, "c:/tmp/BodyComposition-label.nrrd")