ENH: Allow to also use resegmented mask for shape calculation

docs/customization.rst

@@ -190,14 +190,21 @@ Feature Extractor Level
 
 *Resegmentation*
 
-- ``resegmentRange`` [None]: List of 2 floats, specifies the lower and upper threshold, respectively. Segmented voxels
-  outside this range are removed from the mask prior to feature calculation. When the value is None (default), no
-  resegmentation is performed. Resegemented size is checked (using parameter ``minimumROISize``, default 1) and upon
-  fail, an error is logged and the mask is reset to the original mask.
-
-.. note::
-    This only affects first order and texture classes. No resegmentation is performed prior to calculating shape
-    features.
+- ``resegmentRange`` [None]: List of 1 or 2 floats, specifies the lower and and optionally upper threshold,
+  respectively. Segmented voxels outside this range are removed from the mask prior to feature calculation. When the
+  value is None (default), no resegmentation is performed. Resegemented size is checked (using parameter
+  ``minimumROISize``, default 1) and upon fail, an error is logged and extraction is skipped for this case.
+- ``resegmentMode`` ['absolute']: string, specifying the method to use for defining the resegmentation thresholds:
+  - 'absolute': The resegmentRange values are treated as absolute values, i.e. used directly to perform resegmentation.
+  - 'relative': The resegmentRange values are treated as relative to the maximum in the ROI, i.e. the actual threshold
+    used is defined as :math:`\text{threshold} = \text{value} * X_{max}`.
+  - 'sigma': The resegmentRange values indicate a distance from the mean of the ROI in standard deviations. E.g. to
+    exclude outliers farther from the mean than 3 sigma, specify mode 'sigma' and range [-3, 3]. Threshold is defined as
+    :math:`\text{threshold} = \mu + \text{value} * \sigma`.
+- ``resegmentShape`` [False]: Boolean, if set to True, the resegmented mask is also used for shape calculation. If set
+  to False (default), only first order and texture classes are calculated using the resegmented mask (known in IBSI as
+  the intensity mask). Shape is then calculated using the mask after any optional resampling and corrections (known in
+  IBSI as the morphologic mask).
 
 *Mask validation*
 

radiomics/featureextractor.py

@@ -357,6 +357,8 @@ def execute(self, imageFilepath, maskFilepath, label=None, voxelBased=False):
     """
     geometryTolerance = self.settings.get('geometryTolerance')
     additionalInfo = self.settings.get('additionalInfo', False)
+    resegmentShape = self.settings.get('resegmentShape', False)
+
     if label is not None:
       self.settings['label'] = label
     else:
@@ -413,6 +415,11 @@ def execute(self, imageFilepath, maskFilepath, label=None, voxelBased=False):
       if self.generalInfo is not None:
         self.generalInfo.addMaskElements(image, resegmentedMask, label, 'resegmented')
 
+    # if resegmentShape is True and resegmentation has been enabled, update the mask here to also use the
+    # resegmented mask for shape calculation (e.g. PET resegmentation)
+    if resegmentShape and resegmentedMask is not None:
+      mask = resegmentedMask
+
     if not voxelBased:
       # 3. Add the additional information if enabled
       if self.generalInfo is not None:
@@ -435,8 +442,9 @@ def execute(self, imageFilepath, maskFilepath, label=None, voxelBased=False):
           newFeatureName = 'original_shape_%s' % featureName
           featureVector[newFeatureName] = featureValue
 
-    # Only use resegemented mask for feature classes other than shape
-    if resegmentedMask is not None:
+    # (Default) Only use resegemented mask for feature classes other than shape
+    # can be overridden by specifying `resegmentShape` = True
+    if not resegmentShape and resegmentedMask is not None:
       mask = resegmentedMask
 
     # 6. Calculate other enabled feature classes using enabled image types

radiomics/schemas/paramSchema.yaml

@@ -73,6 +73,8 @@ mapping:
       resegmentMode:
         type: str
         enum: ['absolute', 'relative', 'sigma']
+      resegmentShape:
+        type: bool
       preCrop:
         type: bool
       sigma: