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Make the output DICOM SR instance part of the original study #394

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Nov 22, 2022
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Make the output DICOM SR instance part of the original study #394

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926bc9a
Make the output DICOM SR instance part of the original study
MMelQin Nov 12, 2022
2174f38
Use simple series selection rule on modality and image type
MMelQin Nov 12, 2022
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31 changes: 27 additions & 4 deletions examples/apps/breast_density_classifer_app/app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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():
Expand Down