教学大纲
https://pyradiomics.readthedocs.io/en/latest/
https://discourse.slicer.org/c/community/radiomics/23
提取130个特征
可以输出为Table表格
使用 PyRadiomics 提取的各种特征的定义。它们细分为以下几类：
First Order Statistics(19 features)Shape-based (3D)(16 features)Shape-based (2D)(10 features)Gray Level Cooccurence Matrix(24 features)Gray Level Run Length Matrix(16 features)Gray Level Size Zone Matrix(16 features)Neighbouring Gray Tone Difference Matrix(5 features)Gray Level Dependence Matrix(14 features)
-
通过 pip 安装
-
从源代码安装
-
使用 3D Slicer Radiomics 扩展
-
使用 pyradiomics Docker
Params.yaml配置文件进行了文件归一化，可以提取1800多个特征
Params.yaml (365 字节)
setting:
binWidth: 25
label: 1
normalize: True
interpolator: 'sitkBSpline'
resampledPixelSpacing:
weightingNorm:
imageType:
Original: {}
Wavelet: {}
LoG: {sigma: [0.5, 1.0, 2.0, 3.0, 4.0]}
Square: {}
SquareRoot: {}
Logarithm: {}
Exponential: {}
Gradient: {}
featureClass:
shape:
firstorder:
glcm:
glrlm:
glszm:
gldm:
ngtdm:
