Merge pull request #394 from Project-MONAI/mqin/breast_density

Make the output DICOM SR instance part of the original study

Author: vikashg

examples/apps/breast_density_classifer_app/app.py

@@ -19,22 +19,45 @@ def compose(self):
             "0.1",
             "Center for Augmented Intelligence in Imaging, Mayo Clinic, Florida",
         )
-        my_equipment = EquipmentInfo(manufacturer="MONAI Deploy App SD", manufacturer_model="DICOM SR Writer")
+        my_equipment = EquipmentInfo(manufacturer="MONAI Deploy App SDK", manufacturer_model="DICOM SR Writer")
         my_special_tags = {"SeriesDescription": "Not for clinical use"}
         study_loader_op = DICOMDataLoaderOperator()
-        series_selector_op = DICOMSeriesSelectorOperator(rules="")
+        series_selector_op = DICOMSeriesSelectorOperator(rules=Sample_Rules_Text)
         series_to_vol_op = DICOMSeriesToVolumeOperator()
         classifier_op = ClassifierOperator()
         sr_writer_op = DICOMTextSRWriterOperator(
-            copy_tags=False, model_info=model_info, equipment_info=my_equipment, custom_tags=my_special_tags
-        )
+            copy_tags=True, model_info=model_info, equipment_info=my_equipment, custom_tags=my_special_tags
+        )  # copy_tags=True to use Study and Patient modules of the original input
 
         self.add_flow(study_loader_op, series_selector_op, {"dicom_study_list": "dicom_study_list"})
         self.add_flow(
             series_selector_op, series_to_vol_op, {"study_selected_series_list": "study_selected_series_list"}
         )
         self.add_flow(series_to_vol_op, classifier_op, {"image": "image"})
         self.add_flow(classifier_op, sr_writer_op, {"result_text": "classification_result"})
+        # Pass the Study series to the SR writer for copying tags
+        self.add_flow(series_selector_op, sr_writer_op, {"study_selected_series_list": "study_selected_series_list"})
+
+
+# This is a sample series selection rule in JSON, simply selecting a MG series.
+# If the study has more than 1 MG series, then all of them will be selected.
+# Please see more detail in DICOMSeriesSelectorOperator.
+# For list of string values, e.g. "ImageType": ["PRIMARY", "ORIGINAL"], it is a match if all elements
+# are all in the multi-value attribute of the DICOM series.
+
+Sample_Rules_Text = """
+{
+    "selections": [
+        {
+            "name": "MG Series",
+            "conditions": {
+                "Modality": "(?i)MG",
+                "ImageType": ["PRIMARY"]
+            }
+        }
+    ]
+}
+"""
 
 
 def test():