Merge pull request #337 from JoostJM/add-voxel-based-calculation

ADD: Add voxel-based extraction

examples/exampleSettings/exampleVoxel.yaml

@@ -0,0 +1,17 @@
+
+imageType:
+  Original: {}
+
+featureClass:
+  glcm:
+    - JointEntropy
+
+setting:
+  binWidth: 25
+  force2D: true
+  label: 1
+
+voxelSetting:
+  kernelRadius: 2
+  maskedKernel: true
+  initValue: nan

examples/helloFeatureClass.py

@@ -60,11 +60,11 @@
   print(getattr(firstOrderFeatures, 'get%sFeatureValue' % f).__doc__)
 
 print('Calculating first order features...')
-firstOrderFeatures.calculateFeatures()
+results = firstOrderFeatures.execute()
 print('done')
 
 print('Calculated first order features: ')
-for (key, val) in six.iteritems(firstOrderFeatures.featureValues):
+for (key, val) in six.iteritems(results):
   print('  ', key, ':', val)
 
 #
@@ -79,11 +79,11 @@
   print(getattr(shapeFeatures, 'get%sFeatureValue' % f).__doc__)
 
 print('Calculating Shape features...')
-shapeFeatures.calculateFeatures()
+results = shapeFeatures.execute()
 print('done')
 
 print('Calculated Shape features: ')
-for (key, val) in six.iteritems(shapeFeatures.featureValues):
+for (key, val) in six.iteritems(results):
   print('  ', key, ':', val)
 
 #
@@ -98,11 +98,11 @@
   print(getattr(glcmFeatures, 'get%sFeatureValue' % f).__doc__)
 
 print('Calculating GLCM features...')
-glcmFeatures.calculateFeatures()
+results = glcmFeatures.execute()
 print('done')
 
 print('Calculated GLCM features: ')
-for (key, val) in six.iteritems(glcmFeatures.featureValues):
+for (key, val) in six.iteritems(results):
   print('  ', key, ':', val)
 
 #
@@ -117,11 +117,11 @@
   print(getattr(glrlmFeatures, 'get%sFeatureValue' % f).__doc__)
 
 print('Calculating GLRLM features...')
-glrlmFeatures.calculateFeatures()
+results = glrlmFeatures.execute()
 print('done')
 
 print('Calculated GLRLM features: ')
-for (key, val) in six.iteritems(glrlmFeatures.featureValues):
+for (key, val) in six.iteritems(results):
   print('  ', key, ':', val)
 
 #
@@ -136,11 +136,11 @@
   print(getattr(glszmFeatures, 'get%sFeatureValue' % f).__doc__)
 
 print('Calculating GLSZM features...')
-glszmFeatures.calculateFeatures()
+results = glszmFeatures.execute()
 print('done')
 
 print('Calculated GLSZM features: ')
-for (key, val) in six.iteritems(glszmFeatures.featureValues):
+for (key, val) in six.iteritems(results):
   print('  ', key, ':', val)
 
 #
@@ -151,8 +151,8 @@
   for logImage, imageTypeName, inputKwargs in imageoperations.getLoGImage(image, mask, sigma=sigmaValues):
     logFirstorderFeatures = firstorder.RadiomicsFirstOrder(logImage, mask, **inputKwargs)
     logFirstorderFeatures.enableAllFeatures()
-    logFirstorderFeatures.calculateFeatures()
-    for (key, val) in six.iteritems(logFirstorderFeatures.featureValues):
+    results = logFirstorderFeatures.execute()
+    for (key, val) in six.iteritems(results):
       laplacianFeatureName = '%s_%s' % (imageTypeName, key)
       print('  ', laplacianFeatureName, ':', val)
 #
@@ -162,8 +162,8 @@
   for decompositionImage, decompositionName, inputKwargs in imageoperations.getWaveletImage(image, mask):
     waveletFirstOrderFeaturs = firstorder.RadiomicsFirstOrder(decompositionImage, mask, **inputKwargs)
     waveletFirstOrderFeaturs.enableAllFeatures()
-    waveletFirstOrderFeaturs.calculateFeatures()
+    results = waveletFirstOrderFeaturs.execute()
     print('Calculated firstorder features with wavelet ', decompositionName)
-    for (key, val) in six.iteritems(waveletFirstOrderFeaturs.featureValues):
+    for (key, val) in six.iteritems(results):
       waveletFeatureName = '%s_%s' % (str(decompositionName), key)
       print('  ', waveletFeatureName, ':', val)

examples/helloVoxel.py

@@ -0,0 +1,117 @@
+#!/usr/bin/env python
+
+from __future__ import print_function
+
+import logging
+import os
+
+import SimpleITK as sitk
+import six
+
+import radiomics
+from radiomics import featureextractor
+
+def tqdmProgressbar():
+  """
+  This function will setup the progress bar exposed by the 'tqdm' package.
+  Progress reporting is only used in PyRadiomics for the calculation of GLCM and GLSZM in full python mode, therefore
+  enable GLCM and full-python mode to show the progress bar functionality
+
+  N.B. This function will only work if the 'click' package is installed (not included in the PyRadiomics requirements)
+  """
+  global extractor
+
+  radiomics.setVerbosity(logging.INFO)  # Verbosity must be at least INFO to enable progress bar
+
+  import tqdm
+  radiomics.progressReporter = tqdm.tqdm
+
+def clickProgressbar():
+  """
+  This function will setup the progress bar exposed by the 'click' package.
+  Progress reporting is only used in PyRadiomics for the calculation of GLCM and GLSZM in full python mode, therefore
+  enable GLCM and full-python mode to show the progress bar functionality.
+
+  Because the signature used to instantiate a click progress bar is different from what PyRadiomics expects, we need to
+  write a simple wrapper class to enable use of a click progress bar. In this case we only need to change the 'desc'
+  keyword argument to a 'label' keyword argument.
+
+  N.B. This function will only work if the 'click' package is installed (not included in the PyRadiomics requirements)
+  """
+  global extractor
+
+  # Enable the GLCM class to show the progress bar
+  extractor.enableFeatureClassByName('glcm')
+
+  radiomics.setVerbosity(logging.INFO)  # Verbosity must be at least INFO to enable progress bar
+
+  import click
+
+  class progressWrapper():
+    def __init__(self, iterable, desc=''):
+      # For a click progressbar, the description must be provided in the 'label' keyword argument.
+      self.bar = click.progressbar(iterable, label=desc)
+
+    def __iter__(self):
+      return self.bar.__iter__()  # Redirect to the __iter__ function of the click progressbar
+
+    def __enter__(self):
+      return self.bar.__enter__()  # Redirect to the __enter__ function of the click progressbar
+
+    def __exit__(self, exc_type, exc_value, tb):
+      return self.bar.__exit__(exc_type, exc_value, tb)  # Redirect to the __exit__ function of the click progressbar
+
+  radiomics.progressReporter = progressWrapper
+
+# Get some test data
+testCase = 'lung2'
+# repositoryRoot points to the root of the repository. The following line gets that location if this script is run
+# from it's default location in \pyradiomics\bin. Otherwise, it will point to some (invalid) folder, causing the
+# getTestCase function to fail to find the test case in the repository. In that case, a test case will be downloaded to
+# temporary files and it's location is returned.
+repositoryRoot = os.path.abspath(os.path.join(os.getcwd(), ".."))
+imageName, maskName = radiomics.getTestCase(testCase, repositoryRoot)
+
+# Get the location of the example settings file
+paramsFile = os.path.abspath(r'exampleSettings\exampleVoxel.yaml')
+
+if imageName is None or maskName is None:  # Something went wrong, in this case PyRadiomics will also log an error
+  print('Error getting testcase!')
+  exit()
+
+# Regulate verbosity with radiomics.verbosity
+# radiomics.setVerbosity(logging.INFO)
+
+# Get the PyRadiomics logger (default log-level = INFO
+logger = radiomics.logger
+logger.setLevel(logging.DEBUG)  # set level to DEBUG to include debug log messages in log file
+
+# Write out all log entries to a file
+handler = logging.FileHandler(filename='testLog.txt', mode='w')
+formatter = logging.Formatter("%(levelname)s:%(name)s: %(message)s")
+handler.setFormatter(formatter)
+logger.addHandler(handler)
+
+# Initialize feature extractor using the settings file
+extractor = featureextractor.RadiomicsFeaturesExtractor(paramsFile)
+
+# Uncomment one of these functions to show how PyRadiomics can use the 'tqdm' or 'click' package to report progress when
+# running in full python mode. Assumes the respective package is installed (not included in the requirements)
+
+tqdmProgressbar()
+# clickProgressbar()
+
+print("Active features:")
+for cls, features in six.iteritems(extractor._enabledFeatures):
+  if len(features) == 0:
+    features = [f for f, deprecated in six.iteritems(extractor.getFeatureNames(cls)) if not deprecated]
+  for f in features:
+    print(f)
+    print(getattr(extractor.featureClasses[cls], 'get%sFeatureValue' % f).__doc__)
+
+print("Calculating features")
+featureVector = extractor.execute(imageName, maskName, voxelBased=True)
+
+for featureName in featureVector.keys():
+  sitk.WriteImage(featureVector[featureName], '%s_%s.nrrd' % (testCase, featureName))
+  print('Computed %s, stored as "%s_%s.nrrd"' % (featureName, testCase, featureName))