lassoan

#
# Installation:
# - Save this file as AngleMeasurement.py to a directory on your computer
# - Add the directory to the additional module paths in the Slicer application settings:
#   - Choose in the menu: Edit / Application settings
#   - Click Modules, click >> next to Additional module paths
#   - Click Add, and choose the .py file's location
# - After you restart Slicer, "Angle Measurment" module should show up in Quantification category
#

lassoan

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

import SampleData

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

# Create segmentation

lassoan

# This example script demonstrates how a grow-cut
# operation can be performed without graphical user interface.

# The first half of the script downloads input data and creates seed segments.
# The second half of the script converts segments to merged labelmap (that's the required
# input format for grow-cut filter), computes the complete segmentation, and writes
# results into new segments.

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

lassoan

from __main__ import qt, slicer

#
# MarkupsInfo module
#

class MarkupsInfo:
  def __init__(self, parent):
    import string
    parent.title = "Markups info"

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
#

lassoan

##################
## Written by: Kyle Sunderland
##
## Downloads all files from an assembla project
## Need to change repo_name, api_key, and api_secret for the script to work
##################

$repo_name = "REPO_NAME" # Name of the repo

# personal keys found at: https://app.assembla.com/user/edit/manage_clients

lassoan

import SampleData
sampleDataLogic = SampleData.SampleDataLogic()
masterVolumeNode = sampleDataLogic.downloadMRHead()

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

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

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

import SampleData
import numpy as np

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

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())