lassoan

segmentationNode = slicer.mrmlScene.GetFirstNodeByClass('vtkMRMLSegmentationNode')
# set value to the size of the larges cracks in the segment surfaces
maximumHoleSizeMm = 2.0

############
masterVolumeNode = segmentationNode.GetNodeReference(segmentationNode.GetReferenceImageGeometryReferenceRole())

# Create segment editor to get access to effects
segmentEditorWidget = slicer.qMRMLSegmentEditorWidget()
# To show segment editor widget (useful for debugging):

lassoan

# Create a markups fiducial node and place 6 points then copy paste this code into 3D Slicer's Python console.
# Two circles will be created (one for each 3 points) and the axis will be computed by connecting their centers.
# The circles and the axis is updated as the fiducial point positions are adjusted.

def sphereFrom3Points(markupsNode, startPointIndex):
    """Compute center and radius of 3-point sphere from 3 fiducial points
    source: https://stackoverflow.com/questions/20314306/find-arc-circle-equation-given-three-points-in-space-3d
    """
    import numpy as np
    A = np.zeros(3)

lassoan

# There are several variants of the metric. If you need to compute the metric slice by slice then
# you can use Mask volume effect to create a volume where all voxels are blanked out (set to -1000)
# except the calcifications in the selected vessel and compute the total score using this script.
# (based on Agatston (1990) - https://www.sciencedirect.com/science/article/pii/073510979090282T)
#
# Sample data set is available at:
# https://github.com/lassoan/PublicTestingData/releases/download/data/CardiacAgatstonScore.mrb

def computeAgatstonScore(volumeNode, minimumIntensityThreshold=130, minimumIslandSizeInMm2=1.0, verbose=False):
  import numpy as np

lassoan

# This script randomly warps a 3D volume and adds random translations, rotations,
# and save each resulting 3D volume (and a screenshot for quick overview)
#
# The script can be executed by copy-pasting into 3D Slicer's Python console
# or in a Jupyter notebook running 3D Slicer kernel (provided by SlicerJupyter extension).
#
# Prerequisites:
# - Recent Slicer-4.11 version
# - SlicerIGT extension installed (for random deformations)

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

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

import SampleData

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

# Create segmentation

lassoan

The example was moved to Sandbox extension so that users can more easily install it:

https://github.com/PerkLab/SlicerSandbox/blob/master/LoadRemoteFile/LoadRemoteFile.py

More information: https://github.com/PerkLab/SlicerSandbox/blob/master/README.md#loadremotefile

lassoan

# This script can be used with this example scene:
# https://github.com/lassoan/PublicTestingData/releases/download/data/ColoredVolumeRenderingScene.mrb

volumeNode = getNode('Panoramix-cropped')
segmentationNode = getNode('Panoramix-cropped segmentation')
boostSegmentOpacity = False  # Increase voxel value inside segments to allow making them them more opaque

volumesLogic = slicer.modules.volumes.logic()

segmentIds = vtk.vtkStringArray()

lassoan

# Convert volume nodes of 3D Slicer to/from xarray and read/write into zarr format

def xarrayFromVolume(volumeNode) -> "xr.DataArray":
    """Convert an volume node to an xarray.DataArray.
    Origin and spacing metadata is preserved in the xarray's coords. The
    Direction is set in the `direction` attribute.
    Dims are labeled as `x`, `y`, `z`, `t`, and `c`.
    This interface is and behavior is experimental and is subject to possible
    future changes."""
    import xarray as xr

lassoan

#
#
#
#
#
#  This example has been completely reworked and converted to a module, now available at:
#
#
#      https://github.com/lassoan/SlicerLineProfile/blob/master/LineProfile/LineProfile.py
#