Add TLG feature for PET modality

pyradiomics_radler/myfirstorder.py

@@ -64,3 +64,29 @@ class MyRadiomicsFirstOrder(MyRadiomicsFeaturesBase):
 
         return numpy.mean(ROIPet[~numpy.isnan(ROIPet)])
 
+    def getTLGFeatureValue(self):
+        r"""
+        **21. TLG**
+
+        Total lesion glycolysis. 
+        Defined as 
+        
+        .. math::
+        \textit{SUVMean}\times \textit{total volume of the tumour region}
+    
+        - input: 3D array representing the PET volume in SUV format, with 
+                voxels outside the ROI set to NaNs.
+    
+        .. note::
+        Extracted from PET scans and not used in the CT feature set.
+        """
+        z, y, x = self.pixelSpacing
+        Np = len(self.labelledVoxelCoordinates[0])
+        volume = Np * (z * x * y)
+
+        ROIPet = self.imageArray
+        mask = self.maskArray
+        ROIPet[~mask] = numpy.nan
+
+        return numpy.mean(ROIPet[~numpy.isnan(ROIPet)]) * volume
+