Esempio n. 1
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    'owner': 'kaapana',
    '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
Esempio n. 2
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    'retry_delay': timedelta(seconds=60)
}

dag = DAG(dag_id='nnunet-predict',
          default_args=args,
          concurrency=10,
          max_active_runs=10,
          schedule_interval=None)

get_input = LocalGetInputDataOperator(dag=dag,
                                      parallel_downloads=5,
                                      check_modality=True)
get_task_model = GetTaskModelOperator(dag=dag)
# get_task_model = GetContainerModelOperator(dag=dag)
dcm2nifti = DcmConverterOperator(dag=dag,
                                 input_operator=get_input,
                                 output_format='nii.gz')

nnunet_predict = NnUnetOperator(dag=dag,
                                mode="inference",
                                input_nifti_operators=[dcm2nifti],
                                inf_preparation=True,
                                inf_threads_prep=1,
                                inf_threads_nifti=1)

resample_seg = ResampleOperator(
    dag=dag,
    input_operator=nnunet_predict,
    original_img_operator=dcm2nifti,
    operator_out_dir=nnunet_predict.operator_out_dir)
Esempio n. 3
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    'ui_forms': ui_forms,
    'owner': 'kaapana',
    'start_date': days_ago(0),
    'retries': 1,
    'retry_delay': timedelta(seconds=30)
}

dag = DAG(dag_id='radiomics-dcmseg',
          default_args=args,
          schedule_interval=None,
          concurrency=30,
          max_active_runs=15)

get_input = LocalGetInputDataOperator(dag=dag, check_modality=True)
dcmseg2nrrd = DcmSeg2ItkOperator(dag=dag)
get_dicom = LocalGetRefSeriesOperator(dag=dag)
dcm2nrrd = DcmConverterOperator(dag=dag,
                                input_operator=get_dicom,
                                output_format='nrrd')
radiomics = RadiomicsOperator(dag=dag,
                              mask_operator=dcmseg2nrrd,
                              input_operator=dcm2nrrd)
put_radiomics_to_minio = LocalMinioOperator(dag=dag,
                                            action='put',
                                            action_operators=[radiomics],
                                            file_white_tuples=('.xml'))
clean = LocalWorkflowCleanerOperator(dag=dag)

get_input >> dcmseg2nrrd >> radiomics
get_input >> get_dicom >> dcm2nrrd >> radiomics >> put_radiomics_to_minio >> clean
Esempio n. 4
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                "type": "boolean",
                "default": False,
                "readOnly": False,
            }
        }
    }
}

args = {
    'ui_forms': ui_forms,
    'ui_visible': True,
    'owner': 'kaapana',
    'start_date': days_ago(0),
    'retries': 0,
    'retry_delay': timedelta(seconds=30)
}

dag = DAG(dag_id='example-dcm2nrrd', default_args=args, schedule_interval=None)

get_input = LocalGetInputDataOperator(dag=dag)
convert = DcmConverterOperator(dag=dag,
                               input_operator=get_input,
                               output_format='nrrd')
put_to_minio = LocalMinioOperator(dag=dag,
                                  action='put',
                                  action_operators=[convert],
                                  file_white_tuples=('.nrrd'))
clean = LocalWorkflowCleanerOperator(dag=dag, clean_workflow_dir=True)

get_input >> convert >> put_to_minio >> clean
Esempio n. 5
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from kaapana.operators.LocalWorkflowCleanerOperator import LocalWorkflowCleanerOperator
from kaapana.operators.LocalMinioOperator import LocalMinioOperator


log = LoggingMixin().log


args = {
    'ui_visible': True,
    'owner': 'kaapana',
    'start_date': days_ago(0),
    'retries': 0,
    'retry_delay': timedelta(seconds=30)
}

dag = DAG(
    dag_id='example-dcm2nrrd',
    default_args=args,
    schedule_interval=None
    )


get_input = LocalGetInputDataOperator(dag=dag)
convert = DcmConverterOperator(dag=dag, output_format='nrrd')
put_to_minio = LocalMinioOperator(dag=dag, action='put', action_operators=[convert], file_white_tuples=('.nrrd'))
clean = LocalWorkflowCleanerOperator(dag=dag)

get_input >> convert >> put_to_minio >> clean


    input_operator=get_input,
    output_format="nii.gz",
    seg_filter=seg_filter,
    parallel_id='seg',
)

get_ref_ct_series_from_seg = LocalGetRefSeriesOperator(
    dag=dag,
    input_operator=get_input,
    search_policy="reference_uid",
    parallel_downloads=5,
    modality=None
)
dcm2nifti_ct = DcmConverterOperator(
    dag=dag,
    input_operator=get_ref_ct_series_from_seg,
    parallel_id='ct',
    output_format='nii.gz'
)

resample_seg = ResampleOperator(
    dag=dag,
    input_operator=dcm2nifti_seg,
    original_img_operator=dcm2nifti_ct,
    operator_out_dir=dcm2nifti_seg.operator_out_dir
)

check_seg = LocalSegCheckOperator(
    dag=dag,
    abort_on_error=True,
    move_data=False,
    input_operators=[dcm2nifti_seg, dcm2nifti_ct]