Radiomics组学分析初始化

 Radiomics：安装并调通第一个demo

import radiomics
import radiomics.featureextractor as FEE
 
# 文件名
main_path =  './'
ori_name = 'brain1_image.nrrd'
lab_name = 'brain1_label.nrrd'
para_name = 'default.yaml'
 
# 文件全部路径
ori_path = main_path + ori_name  
lab_path = main_path + lab_name
para_path = main_path + para_name
print("originl path: " + ori_path)
print("label path: " + lab_path)
print("parameter path: " + para_path)
 
# 使用配置文件初始化特征抽取器
extractor = FEE.RadiomicsFeatureExtractor(para_path)

print("Extraction parameters:\n\t", extractor.settings)
print("Enabled filters:\n\t", extractor.enabledImagetypes)
print("Enabled filters:\n\t", extractor.enabledFeatures)

# 运行
result = extractor.execute(ori_path,lab_path)  #抽取特征
print ("Result type:", type(result))  # result is returned in a Python ordered dictionary
print ("")
print ("Calculated features")
for key, value in result.items():  #输出特征
    print ("\t", key, ":", value)

测试图像下载：https://pan.baidu.com/s/1KvPmJnk88kkdI_0IOCMRMQ 提取码: 4hp5， default.yaml内容如下：

# This is an example of a parameters file
# It is written according to the YAML-convention (www.yaml.org) and is checked by the code for consistency.
# Three types of parameters are possible and reflected in the structure of the document:
#
# Parameter category:
#   Setting Name: 
#
# The three parameter categories are:
# - setting: Setting to use for preprocessing and class specific settings. if no  is specified, the value for
#   this setting is set to None.
# - featureClass: Feature class to enable,  is list of strings representing enabled features. If no  is
#   specified or  is an empty list ('[]'), all features for this class are enabled.
# - imageType: image types to calculate features on.  is custom kwarg settings (dictionary). if  is an
#   empty dictionary ('{}'), no custom settings are added for this input image.
#
# Some parameters have a limited list of possible values. Where this is the case, possible values are listed in the
# package documentation

# Settings to use, possible settings are listed in the documentation (section "Customizing the extraction").
setting:
  binWidth: 25
  label: 1
  interpolator: 'sitkBSpline' # This is an enumerated value, here None is not allowed
  resampledPixelSpacing: # This disables resampling, as it is interpreted as None, to enable it, specify spacing in x, y, z as [x, y , z]
  weightingNorm: # If no value is specified, it is interpreted as None
  force2D: true
  force2Ddimension: 0  # axial slices, for coronal slices, use dimension 1 and for sagittal, dimension 2.
# Image types to use: "Original" for unfiltered image, for possible filters, see documentation.
imageType:
  Original: {} # for dictionaries / mappings, None values are not allowed, '{}' is interpreted as an empty dictionary
  # LoG:{'sigma': [1.0, 3.0]}
  Wavelet:
    binWidth: 10
# Featureclasses, from which features must be calculated. If a featureclass is not mentioned, no features are calculated
# for that class. Otherwise, the specified features are calculated, or, if none are specified, all are calculated (excluding redundant/deprecated features).
featureClass:
  shape:
  # redundant Compactness 1, Compactness 2 an Spherical Disproportion features are disabled by default, they can be
  # enabled by specifying individual feature names (as is done for glcm) and including them in the list.
  shape:
    - SurfaceArea
  firstorder: [] # specifying an empty list has the same effect as specifying nothing.
  glcm:  # Disable SumAverage by specifying all other GLCM features available
    - 'Autocorrelation'
    - 'JointAverage'
    - 'ClusterProminence'
    - 'ClusterShade'
    - 'ClusterTendency'
    - 'Contrast'
    - 'DifferenceVariance'
    - 'JointEnergy'
    - 'JointEntropy'
  glrlm: # for lists none values are allowed, in this case, all features are enabled
  glszm:
  gldm:  # contains deprecated features, but as no individual features are specified, the deprecated features are not enabled

结果：（一大堆冗余数据，还需后续分析）