'start_date': days_ago(0),
'retries': 0,
'retry_delay': timedelta(seconds=60)
}
dag = DAG(dag_id='nnunet-predict',
default_args=args,
concurrency=50,
max_active_runs=30,
schedule_interval=None)
get_input = LocalGetInputDataOperator(dag=dag, check_modality=True)
get_task_model = GetTaskModelOperator(dag=dag)
# get_task_model = GetContainerModelOperator(dag=dag)
dcm2nifti = DcmConverterOperator(dag=dag, output_format='nii.gz')
nnunet_predict = NnUnetOperator(dag=dag,
input_dirs=[dcm2nifti.operator_out_dir],
input_operator=dcm2nifti)
alg_name = nnunet_predict.image.split("/")[-1].split(":")[0]
nrrd2dcmSeg_multi = Itk2DcmSegOperator(dag=dag,
segmentation_operator=nnunet_predict,
input_type="multi_label_seg",
multi_label_seg_name=alg_name,
alg_name=alg_name)
dcmseg_send_multi = DcmSendOperator(dag=dag, input_operator=nrrd2dcmSeg_multi)
clean = LocalWorkflowCleanerOperator(dag=dag)
get_input >> get_task_model >> dcm2nifti >> nnunet_predict >> nrrd2dcmSeg_multi >> dcmseg_send_multi >> clean
from kaapana.operators.LocalGetInputDataOperator import LocalGetInputDataOperator
from kaapana.operators.LocalWorkflowCleanerOperator import LocalWorkflowCleanerOperator
log = LoggingMixin().log
args = {
'ui_visible': False,
'owner': 'kaapana',
'start_date': days_ago(0),
'retries': 2,
'retry_delay': timedelta(seconds=30),
}
dag = DAG(
dag_id='service-minio-dicom-upload',
default_args=args,
schedule_interval=None,
concurrency=10,
max_active_runs=5
)
get_object_from_minio = LocalMinioOperator(dag=dag, action_operator_dirs=['dicoms'], operator_out_dir='dicoms')
unzip_files = LocalUnzipFileOperator(dag=dag, input_operator=get_object_from_minio)
dicom_send = DcmSendOperator(dag=dag, input_operator=unzip_files, ae_title='uploaded', level='batch')
remove_object_from_minio = LocalMinioOperator(dag=dag, parallel_id='removing', action='remove', trigger_rule=TriggerRule.ALL_DONE)
clean = LocalWorkflowCleanerOperator(dag=dag,clean_workflow_dir=True)
get_object_from_minio >> unzip_files >> dicom_send >> remove_object_from_minio >> clean
log = LoggingMixin().log
args = {
'owner': 'kaapana',
'start_date': days_ago(0),
'retries': 2,
'retry_delay': timedelta(seconds=30),
}
dag = DAG(dag_id='minio-seg-to-pacs',
default_args=args,
schedule_interval=None)
#predefine the bucketname and segmentation folder
bucket_name = 'pacs-dicom-data'
upload_folder_tree = 'segmentation_tree'
pull_object_from_minio = LocalMinioOperator(
dag=dag,
bucket_name=bucket_name,
action_operator_dirs=[upload_folder_tree],
operator_out_dir=upload_folder_tree,
file_white_tuples='.dcm',
split_level=1)
dicom_send = DcmSendOperator(dag=dag,
input_operator=pull_object_from_minio,
ae_title='mitk-seg',
level='pile')
clean = LocalWorkflowCleanerOperator(dag=dag)
pull_object_from_minio >> dicom_send >> clean
single_label_seg_info="Right@Kidney",
parallel_id='kidney-right',
alg_name=alg_name,
series_description=f'{alg_name} - Kidney-Right'
)
nrrd2dcmSeg_kidney_left = Itk2DcmSegOperator(
dag=dag,
input_operator=get_input,
segmentation_operator=organSeg_kidney_left,
single_label_seg_info="Left@Kidney",
parallel_id='kidney-left',
alg_name=alg_name,
series_description=f'{alg_name} - Kidney-Left'
)
# Send DICOM segmentation objects to pacs
dcmseg_send_liver = DcmSendOperator(dag=dag, input_operator=nrrd2dcmSeg_liver)
dcmseg_send_spleen = DcmSendOperator(dag=dag, input_operator=nrrd2dcmSeg_spleen)
dcmseg_send_kidney_right = DcmSendOperator(dag=dag, input_operator=nrrd2dcmSeg_kidney_right)
dcmseg_send_kidney_left = DcmSendOperator(dag=dag, input_operator=nrrd2dcmSeg_kidney_left)
clean = LocalWorkflowCleanerOperator(dag=dag, clean_workflow_dir=True)
get_input >> dcm2nrrd >> organSeg_unityCS
organSeg_unityCS >> organSeg_liver >> nrrd2dcmSeg_liver >> dcmseg_send_liver >> clean
organSeg_unityCS >> organSeg_spleen >> nrrd2dcmSeg_spleen >> dcmseg_send_spleen >> clean
organSeg_spleen >> organSeg_kidney_right >> nrrd2dcmSeg_kidney_right >> dcmseg_send_kidney_right >> clean
organSeg_spleen >> organSeg_kidney_left >> nrrd2dcmSeg_kidney_left >> dcmseg_send_kidney_left >> clean
"ui_visible": True,
}
args = {
'owner': 'kaapana',
'start_date': days_ago(0),
'retries': 0,
'dag_info': dag_info,
'retry_delay': timedelta(seconds=30)
}
dag = DAG(dag_id='mitk-flow',
default_args=args,
concurrency=10,
max_active_runs=5,
schedule_interval=None)
get_input = LocalGetInputDataOperator(dag=dag)
mitk_input = MitkInputOperator(dag=dag, input_operator=get_input)
launch_app = KaapanaApplicationOperator(dag=dag,
name="application-mitk-flow",
chart_name='mitk-flow-chart',
version='2020-12-01-vdev')
send_dicom = DcmSendOperator(dag=dag,
input_operator=launch_app,
ae_title="MITK-flow")
clean = LocalWorkflowCleanerOperator(dag=dag)
get_input >> mitk_input >> launch_app >> send_dicom >> clean
}
}
args = {
'ui_visible': True,
'ui_forms': ui_forms,
'owner': 'kaapana',
'start_date': days_ago(0),
'retries': 0,
'retry_delay': timedelta(seconds=30)
}
dag = DAG(dag_id='send-dicom',
default_args=args,
concurrency=10,
max_active_runs=10,
schedule_interval=None)
get_input = LocalGetInputDataOperator(dag=dag)
dcm_send = DcmSendOperator(dag=dag,
input_operator=get_input,
ae_title=ae_title,
pacs_host=pacs_host,
pacs_port=pacs_port,
host_network=True,
level='element')
clean = LocalWorkflowCleanerOperator(dag=dag, clean_workflow_dir=True)
get_input >> dcm_send >> clean
default_args=args,
schedule_interval=None,
concurrency=30,
max_active_runs=15)
get_input = LocalGetInputDataOperator(dag=dag, check_modality=True)
dcmseg2nrrd = DcmSeg2ItkOperator(dag=dag, input_operator=get_input)
get_dicom = LocalGetRefSeriesOperator(dag=dag, input_operator=get_input)
dcm2nrrd = DcmConverterOperator(dag=dag,
input_operator=get_dicom,
output_format='nrrd')
radiomics = RadiomicsOperator(dag=dag,
mask_operator=dcmseg2nrrd,
input_operator=dcm2nrrd)
stats2pdf = Statistics2PdfOperator(dag=dag, input_operator=radiomics)
pdf2dcm = Pdf2DcmOperator(dag=dag,
dicom_operator=get_input,
input_operator=stats2pdf,
pdf_title="Radiomics Report")
dcm_pdf_send = DcmSendOperator(dag=dag, input_operator=pdf2dcm)
put_radiomics_to_minio = LocalMinioOperator(dag=dag,
action='put',
action_operators=[radiomics],
file_white_tuples=('.xml'))
clean = LocalWorkflowCleanerOperator(dag=dag, clean_workflow_dir=True)
get_input >> dcmseg2nrrd >> radiomics >> stats2pdf >> pdf2dcm >> dcm_pdf_send >> clean
get_input >> get_dicom >> dcm2nrrd >> radiomics >> put_radiomics_to_minio >> clean
input_operator=nnunet_preprocess,
train_network=train_network,
train_network_trainer=train_network_trainer,
retries=0
)
bin2dcm = Bin2DcmOperator(
dag=dag,
input_operator=nnunet_export,
study_uid=study_uid,
file_extensions="*.zip"
)
dcmseg_send = DcmSendOperator(
dag=dag,
level="batch",
ae_title="nnunet-models",
input_operator=bin2dcm
)
clean = LocalWorkflowCleanerOperator(dag=dag, clean_workflow_dir=True)
get_input >> dcm2nifti_seg >> resample_seg >> check_seg >> nnunet_preprocess
get_input >> get_ref_ct_series_from_seg >> dcm2nifti_ct >> resample_seg >> check_seg >> nnunet_preprocess
nnunet_preprocess >> nnunet_train_fold0 >> identify_best
nnunet_preprocess >> nnunet_train_fold1 >> identify_best
nnunet_preprocess >> nnunet_train_fold2 >> identify_best
nnunet_preprocess >> nnunet_train_fold3 >> identify_best
nnunet_preprocess >> nnunet_train_fold4 >> identify_best
identify_best >> nnunet_export >> bin2dcm >> dcmseg_send >> clean
train_max_epochs=1000,
input_operator=nnunet_preprocess,
train_network=train_network,
train_network_trainer=train_network_trainer,
train_fold='all',
retries=0)
pdf2dcm = Pdf2DcmOperator(dag=dag,
input_operator=nnunet_train,
study_uid=study_uid,
aetitle=ae_title,
pdf_title=f"Training Report nnUNet {timestamp}")
dcmseg_send_pdf = DcmSendOperator(dag=dag,
parallel_id="pdf",
level="batch",
ae_title=ae_title,
input_operator=pdf2dcm)
zip_model = ZipUnzipOperator(
dag=dag,
target_filename=f"nnunet_model_{train_network}.zip",
whitelist_files=
"model_latest.model.pkl,model_latest.model,model_final_checkpoint.model,model_final_checkpoint.model.pkl,*.png,*.json,*.txt,*.pdf",
subdir="results/nnUNet",
mode="zip",
batch_level=True,
input_operator=nnunet_train)
bin2dcm = Bin2DcmOperator(dag=dag,
name="model2dicom",