Add SUVMax and SUVMean features for PET modality

pyradiomics_radler/myfirstorder.py

+import numpy
+from scipy import ndimage
+
+from radiomics.firstorder import RadiomicsFirstOrder
+from .mybase import MyRadiomicsFeaturesBase
+
+
+class MyRadiomicsFirstOrder(MyRadiomicsFeaturesBase):
+    def __init__(self, inputImage, inputMask, **kwargs):
+        super().__init__(inputImage, inputMask, **kwargs)
+
+        self.pixelSpacing = inputImage.GetSpacing()
+        self.voxelArrayShift = kwargs.get('voxelArrayShift', 0)
+
+    def _initCalculation(self):
+        return super()._initSegmentBasedCalculation()
+
+        self.targetVoxelArray = self.imageArray[self.labelledVoxelCoordinates].astype(
+            'float'
+        )
+        self.discretizedTargetVoxelArray = None  # Lazy instantiation
+
+        self.logger.debug('First order feature class initialized')
+
+    def _moment(self, a, moment=1, axis=0):
+        return RadiomicsFirstOrder._moment(self, a, moment, axis)
+
+    def _getDiscretizedTargetVoxelArray(self):
+        return RadiomicsFirstOrder._getDiscretizedTargetVoxelArray(self)
+
+    def getSuvMaxFeatureValue(self):
+        r"""
+        **20. SUV max**
+
+        Implemented as one of the intensity features extracted by Vallieres et al.
+        Maximum SUV of the tumour region. 
+
+        - input: 3D array representing the PET volume in SUV format
+
+        .. note::
+        Extracted from PET scans and not used in the CT feature set.
+        """
+        ROIPet = self.imageArray
+        mask = self.maskArray
+        ROIPet[~mask] = numpy.nan
+
+        return numpy.max(ROIPet[~numpy.isnan(ROIPet)])
+
+    def getSuvMeanFeatureValue(self):
+        r"""
+        **21. SUV mean**
+
+        Implemented as one of the intensity features extracted by valieres et al.
+        Average SUV of the tumour region. 
+
+        - input: 3D array representing the PET volume in SUV format
+
+        .. note::
+        Extracted from PET scans and not used in the CT feature set.
+        """
+        ROIPet = self.imageArray
+        mask = self.maskArray
+        ROIPet[~mask] = numpy.nan
+
+        return numpy.mean(ROIPet[~numpy.isnan(ROIPet)])
+