HealthImaging ejemplos que utilizan el SDK para Python (Boto3)

import logging
import boto3
from botocore.exceptions import ClientError

logger = logging.getLogger(__name__)


def hello_medical_imaging(medical_imaging_client):
    """
    Use the AWS SDK for Python (Boto3) to create an AWS HealthImaging
    client and list the data stores in your account.
    This example uses the default settings specified in your shared credentials
    and config files.

    :param medical_imaging_client: A Boto3 AWS HealthImaging Client object.
    """
    print("Hello, Amazon Health Imaging! Let's list some of your data stores:\n")
    try:
        paginator = medical_imaging_client.get_paginator("list_datastores")
        page_iterator = paginator.paginate()
        datastore_summaries = []
        for page in page_iterator:
            datastore_summaries.extend(page["datastoreSummaries"])
        print("\tData Stores:")
        for ds in datastore_summaries:
            print(f"\t\tDatastore: {ds['datastoreName']} ID {ds['datastoreId']}")
    except ClientError as err:
        logger.error(
            "Couldn't list data stores. Here's why: %s: %s",
            err.response["Error"]["Code"],
            err.response["Error"]["Message"],
        )
        raise


if __name__ == "__main__":
    hello_medical_imaging(boto3.client("medical-imaging"))

Función de utilidad para copiar un conjunto de imágenes.

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def copy_image_set(
        self,
        datastore_id,
        image_set_id,
        version_id,
        destination_image_set_id=None,
        destination_version_id=None,
        force=False,
        subsets=[],
    ):
        """
        Copy an image set.

        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :param version_id: The ID of the image set version.
        :param destination_image_set_id: The ID of the optional destination image set.
        :param destination_version_id: The ID of the optional destination image set version.
        :param force: Force the copy.
        :param subsets: The optional subsets to copy. For example: ["12345678901234567890123456789012"].
        :return: The copied image set ID.
        """
        try:
            copy_image_set_information = {
                "sourceImageSet": {"latestVersionId": version_id}
            }
            if destination_image_set_id and destination_version_id:
                copy_image_set_information["destinationImageSet"] = {
                    "imageSetId": destination_image_set_id,
                    "latestVersionId": destination_version_id,
                }
            if len(subsets) > 0:
                copySubsetsJson = {
                    "SchemaVersion": "1.1",
                    "Study": {"Series": {"imageSetId": {"Instances": {}}}},
                }

                for subset in subsets:
                    copySubsetsJson["Study"]["Series"]["imageSetId"]["Instances"][
                        subset
                    ] = {}

                copy_image_set_information["sourceImageSet"]["DICOMCopies"] = {
                    "copiableAttributes": json.dumps(copySubsetsJson)
                }
            copy_results = self.health_imaging_client.copy_image_set(
                datastoreId=datastore_id,
                sourceImageSetId=image_set_id,
                copyImageSetInformation=copy_image_set_information,
                force=force,
            )
        except ClientError as err:
            logger.error(
                "Couldn't copy image set. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return copy_results["destinationImageSetProperties"]["imageSetId"]

Copiar un conjunto de imágenes sin destino.

            copy_image_set_information = {
                "sourceImageSet": {"latestVersionId": version_id}
            }

            copy_results = self.health_imaging_client.copy_image_set(
                datastoreId=datastore_id,
                sourceImageSetId=image_set_id,
                copyImageSetInformation=copy_image_set_information,
                force=force,
            )

Copie un conjunto de imágenes con un destino.

            copy_image_set_information = {
                "sourceImageSet": {"latestVersionId": version_id}
            }

            if destination_image_set_id and destination_version_id:
                copy_image_set_information["destinationImageSet"] = {
                    "imageSetId": destination_image_set_id,
                    "latestVersionId": destination_version_id,
                }

            copy_results = self.health_imaging_client.copy_image_set(
                datastoreId=datastore_id,
                sourceImageSetId=image_set_id,
                copyImageSetInformation=copy_image_set_information,
                force=force,
            )

Copia un subconjunto de un conjunto de imágenes.

            copy_image_set_information = {
                "sourceImageSet": {"latestVersionId": version_id}
            }

            if len(subsets) > 0:
                copySubsetsJson = {
                    "SchemaVersion": "1.1",
                    "Study": {"Series": {"imageSetId": {"Instances": {}}}},
                }

                for subset in subsets:
                    copySubsetsJson["Study"]["Series"]["imageSetId"]["Instances"][
                        subset
                    ] = {}

                copy_image_set_information["sourceImageSet"]["DICOMCopies"] = {
                    "copiableAttributes": json.dumps(copySubsetsJson)
                }

            copy_results = self.health_imaging_client.copy_image_set(
                datastoreId=datastore_id,
                sourceImageSetId=image_set_id,
                copyImageSetInformation=copy_image_set_information,
                force=force,
            )

El código siguiente crea una instancia del objeto. MedicalImagingWrapper

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def create_datastore(self, name):
        """
        Create a data store.

        :param name: The name of the data store to create.
        :return: The data store ID.
        """
        try:
            data_store = self.health_imaging_client.create_datastore(datastoreName=name)
        except ClientError as err:
            logger.error(
                "Couldn't create data store %s. Here's why: %s: %s",
                name,
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return data_store["datastoreId"]

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def delete_datastore(self, datastore_id):
        """
        Delete a data store.

        :param datastore_id: The ID of the data store.
        """
        try:
            self.health_imaging_client.delete_datastore(datastoreId=datastore_id)
        except ClientError as err:
            logger.error(
                "Couldn't delete data store %s. Here's why: %s: %s",
                datastore_id,
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def delete_image_set(self, datastore_id, image_set_id):
        """
        Delete an image set.

        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :return: The delete results.
        """
        try:
            delete_results = self.health_imaging_client.delete_image_set(
                imageSetId=image_set_id, datastoreId=datastore_id
            )
        except ClientError as err:
            logger.error(
                "Couldn't delete image set. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return delete_results

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def get_dicom_import_job(self, datastore_id, job_id):
        """
        Get the properties of a DICOM import job.

        :param datastore_id: The ID of the data store.
        :param job_id: The ID of the job.
        :return: The job properties.
        """
        try:
            job = self.health_imaging_client.get_dicom_import_job(
                jobId=job_id, datastoreId=datastore_id
            )
        except ClientError as err:
            logger.error(
                "Couldn't get DICOM import job. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return job["jobProperties"]

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def get_datastore_properties(self, datastore_id):
        """
        Get the properties of a data store.

        :param datastore_id: The ID of the data store.
        :return: The data store properties.
        """
        try:
            data_store = self.health_imaging_client.get_datastore(
                datastoreId=datastore_id
            )
        except ClientError as err:
            logger.error(
                "Couldn't get data store %s. Here's why: %s: %s",
                id,
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return data_store["datastoreProperties"]

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def get_pixel_data(
        self, file_path_to_write, datastore_id, image_set_id, image_frame_id
    ):
        """
        Get an image frame's pixel data.

        :param file_path_to_write: The path to write the image frame's HTJ2K encoded pixel data.
        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :param image_frame_id: The ID of the image frame.
        """
        try:
            image_frame = self.health_imaging_client.get_image_frame(
                datastoreId=datastore_id,
                imageSetId=image_set_id,
                imageFrameInformation={"imageFrameId": image_frame_id},
            )
            with open(file_path_to_write, "wb") as f:
                for chunk in image_frame["imageFrameBlob"].iter_chunks():
                    if chunk:
                        f.write(chunk)
        except ClientError as err:
            logger.error(
                "Couldn't get image frame. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def get_image_set(self, datastore_id, image_set_id, version_id=None):
        """
        Get the properties of an image set.

        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :param version_id: The optional version of the image set.
        :return: The image set properties.
        """
        try:
            if version_id:
                image_set = self.health_imaging_client.get_image_set(
                    imageSetId=image_set_id,
                    datastoreId=datastore_id,
                    versionId=version_id,
                )
            else:
                image_set = self.health_imaging_client.get_image_set(
                    imageSetId=image_set_id, datastoreId=datastore_id
                )
        except ClientError as err:
            logger.error(
                "Couldn't get image set. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return image_set

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

Función de utilidad para obtener metadatos del conjunto de imágenes.

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def get_image_set_metadata(
        self, metadata_file, datastore_id, image_set_id, version_id=None
    ):
        """
        Get the metadata of an image set.

        :param metadata_file: The file to store the JSON gzipped metadata.
        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :param version_id: The version of the image set.
        """
        try:
            if version_id:
                image_set_metadata = self.health_imaging_client.get_image_set_metadata(
                    imageSetId=image_set_id,
                    datastoreId=datastore_id,
                    versionId=version_id,
                )
            else:

                image_set_metadata = self.health_imaging_client.get_image_set_metadata(
                    imageSetId=image_set_id, datastoreId=datastore_id
                )
            print(image_set_metadata)
            with open(metadata_file, "wb") as f:
                for chunk in image_set_metadata["imageSetMetadataBlob"].iter_chunks():
                    if chunk:
                        f.write(chunk)

        except ClientError as err:
            logger.error(
                "Couldn't get image metadata. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

Obtener metadatos del conjunto de imágenes sin versión.

                image_set_metadata = self.health_imaging_client.get_image_set_metadata(
                    imageSetId=image_set_id, datastoreId=datastore_id
                )

Obtener metadatos del conjunto de imágenes con la versión.

                image_set_metadata = self.health_imaging_client.get_image_set_metadata(
                    imageSetId=image_set_id,
                    datastoreId=datastore_id,
                    versionId=version_id,
                )

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def list_dicom_import_jobs(self, datastore_id):
        """
        List the DICOM import jobs.

        :param datastore_id: The ID of the data store.
        :return: The list of jobs.
        """
        try:
            paginator = self.health_imaging_client.get_paginator(
                "list_dicom_import_jobs"
            )
            page_iterator = paginator.paginate(datastoreId=datastore_id)
            job_summaries = []
            for page in page_iterator:
                job_summaries.extend(page["jobSummaries"])
        except ClientError as err:
            logger.error(
                "Couldn't list DICOM import jobs. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return job_summaries

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def list_datastores(self):
        """
        List the data stores.

        :return: The list of data stores.
        """
        try:
            paginator = self.health_imaging_client.get_paginator("list_datastores")
            page_iterator = paginator.paginate()
            datastore_summaries = []
            for page in page_iterator:
                datastore_summaries.extend(page["datastoreSummaries"])
        except ClientError as err:
            logger.error(
                "Couldn't list data stores. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return datastore_summaries

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def list_image_set_versions(self, datastore_id, image_set_id):
        """
        List the image set versions.

        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :return: The list of image set versions.
        """
        try:
            paginator = self.health_imaging_client.get_paginator(
                "list_image_set_versions"
            )
            page_iterator = paginator.paginate(
                imageSetId=image_set_id, datastoreId=datastore_id
            )
            image_set_properties_list = []
            for page in page_iterator:
                image_set_properties_list.extend(page["imageSetPropertiesList"])
        except ClientError as err:
            logger.error(
                "Couldn't list image set versions. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return image_set_properties_list

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def list_tags_for_resource(self, resource_arn):
        """
        List the tags for a resource.

        :param resource_arn: The ARN of the resource.
        :return: The list of tags.
        """
        try:
            tags = self.health_imaging_client.list_tags_for_resource(
                resourceArn=resource_arn
            )
        except ClientError as err:
            logger.error(
                "Couldn't list tags for resource. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return tags["tags"]

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

La función de utilidad para buscar conjuntos de imágenes.

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def search_image_sets(self, datastore_id, search_filter):
        """
        Search for image sets.

        :param datastore_id: The ID of the data store.
        :param search_filter: The search filter.
            For example: {"filters" : [{ "operator": "EQUAL", "values": [{"DICOMPatientId": "3524578"}]}]}.
        :return: The list of image sets.
        """
        try:
            paginator = self.health_imaging_client.get_paginator("search_image_sets")
            page_iterator = paginator.paginate(
                datastoreId=datastore_id, searchCriteria=search_filter
            )
            metadata_summaries = []
            for page in page_iterator:
                metadata_summaries.extend(page["imageSetsMetadataSummaries"])
        except ClientError as err:
            logger.error(
                "Couldn't search image sets. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return metadata_summaries

Caso de uso núm. 1: operador IGUAL.

        search_filter = {
            "filters": [
                {"operator": "EQUAL", "values": [{"DICOMPatientId": patient_id}]}
            ]
        }

        image_sets = self.search_image_sets(data_store_id, search_filter)
        print(f"Image sets found with EQUAL operator\n{image_sets}")

Caso de uso #2: el operador BETWEEN usa DICOMStudy fecha y DICOMStudy hora.

        search_filter = {
            "filters": [
                {
                    "operator": "BETWEEN",
                    "values": [
                        {
                            "DICOMStudyDateAndTime": {
                                "DICOMStudyDate": "19900101",
                                "DICOMStudyTime": "000000",
                            }
                        },
                        {
                            "DICOMStudyDateAndTime": {
                                "DICOMStudyDate": "20230101",
                                "DICOMStudyTime": "000000",
                            }
                        },
                    ],
                }
            ]
        }

        image_sets = self.search_image_sets(data_store_id, search_filter)
        print(
            f"Image sets found with BETWEEN operator using DICOMStudyDate and DICOMStudyTime\n{image_sets}"
        )

Caso de uso núm. 3: el operador ENTRE usa CreatedAt. Los estudios de tiempo se habían mantenido previamente.

        search_filter = {
            "filters": [
                {
                    "values": [
                        {
                            "createdAt": datetime.datetime(
                                2021, 8, 4, 14, 49, 54, 429000
                            )
                        },
                        {
                            "createdAt": datetime.datetime.now()
                            + datetime.timedelta(days=1)
                        },
                    ],
                    "operator": "BETWEEN",
                }
            ]
        }

        recent_image_sets = self.search_image_sets(data_store_id, search_filter)
        print(
            f"Image sets found with with BETWEEN operator using createdAt\n{recent_image_sets}"
        )

Caso de uso #4: operador EQUAL en DICOMSeries InstanceUID y BETWEEN en UpdatedAt y ordena la respuesta en orden ASC en el campo UpdatedAt.

        search_filter = {
            "filters": [
                {
                    "values": [
                        {
                            "updatedAt": datetime.datetime(
                                2021, 8, 4, 14, 49, 54, 429000
                            )
                        },
                        {
                            "updatedAt": datetime.datetime.now()
                            + datetime.timedelta(days=1)
                        },
                    ],
                    "operator": "BETWEEN",
                },
                {
                    "values": [{"DICOMSeriesInstanceUID": series_instance_uid}],
                    "operator": "EQUAL",
                },
            ],
            "sort": {
                "sortOrder": "ASC",
                "sortField": "updatedAt",
            },
        }

        image_sets = self.search_image_sets(data_store_id, search_filter)
        print(
            "Image sets found with EQUAL operator on DICOMSeriesInstanceUID and BETWEEN on updatedAt and"
        )
        print(f"sort response in ASC order on updatedAt field\n{image_sets}")

MedicalImagingWrapper El siguiente código crea una instancia del objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def start_dicom_import_job(
        self, job_name, datastore_id, role_arn, input_s3_uri, output_s3_uri
    ):
        """
        Start a DICOM import job.

        :param job_name: The name of the job.
        :param datastore_id: The ID of the data store.
        :param role_arn: The Amazon Resource Name (ARN) of the role to use for the job.
        :param input_s3_uri: The S3 bucket input prefix path containing the DICOM files.
        :param output_s3_uri: The S3 bucket output prefix path for the result.
        :return: The job ID.
        """
        try:
            job = self.health_imaging_client.start_dicom_import_job(
                jobName=job_name,
                datastoreId=datastore_id,
                dataAccessRoleArn=role_arn,
                inputS3Uri=input_s3_uri,
                outputS3Uri=output_s3_uri,
            )
        except ClientError as err:
            logger.error(
                "Couldn't start DICOM import job. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return job["jobId"]

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def tag_resource(self, resource_arn, tags):
        """
        Tag a resource.

        :param resource_arn: The ARN of the resource.
        :param tags: The tags to apply.
        """
        try:
            self.health_imaging_client.tag_resource(resourceArn=resource_arn, tags=tags)
        except ClientError as err:
            logger.error(
                "Couldn't tag resource. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def untag_resource(self, resource_arn, tag_keys):
        """
        Untag a resource.

        :param resource_arn: The ARN of the resource.
        :param tag_keys: The tag keys to remove.
        """
        try:
            self.health_imaging_client.untag_resource(
                resourceArn=resource_arn, tagKeys=tag_keys
            )
        except ClientError as err:
            logger.error(
                "Couldn't untag resource. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def update_image_set_metadata(
        self, datastore_id, image_set_id, version_id, metadata, force=False
    ):
        """
        Update the metadata of an image set.

        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :param version_id: The ID of the image set version.
        :param metadata: The image set metadata as a dictionary.
            For example {"DICOMUpdates": {"updatableAttributes":
            "{\"SchemaVersion\":1.1,\"Patient\":{\"DICOM\":{\"PatientName\":\"Garcia^Gloria\"}}}"}}
        :param: force: Force the update.
        :return: The updated image set metadata.
        """
        try:
            updated_metadata = self.health_imaging_client.update_image_set_metadata(
                imageSetId=image_set_id,
                datastoreId=datastore_id,
                latestVersionId=version_id,
                updateImageSetMetadataUpdates=metadata,
                force=force,
            )
        except ClientError as err:
            logger.error(
                "Couldn't update image set metadata. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return updated_metadata

El siguiente código crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

Caso de uso #1: inserta o actualiza un atributo.

            attributes = """{
                    "SchemaVersion": 1.1,
                    "Study": {
                        "DICOM": {
                            "StudyDescription": "CT CHEST"
                        }
                    }
                }"""
            metadata = {"DICOMUpdates": {"updatableAttributes": attributes}}

            self.update_image_set_metadata(
                data_store_id, image_set_id, version_id, metadata, force
            )

Caso de uso #2: eliminar un atributo.

            # Attribute key and value must match the existing attribute.
            attributes = """{
                    "SchemaVersion": 1.1,
                    "Study": {
                        "DICOM": {
                            "StudyDescription": "CT CHEST"
                        }
                    }
                }"""
            metadata = {"DICOMUpdates": {"removableAttributes": attributes}}

            self.update_image_set_metadata(
                data_store_id, image_set_id, version_id, metadata, force
            )

Caso de uso #3: eliminar una instancia.

            attributes = """{
                    "SchemaVersion": 1.1,
                    "Study": {
                        "Series": {
                            "1.1.1.1.1.1.12345.123456789012.123.12345678901234.1": {
                                "Instances": {
                                    "1.1.1.1.1.1.12345.123456789012.123.12345678901234.1": {}
                                }
                            }
                        }
                    }
                }"""
            metadata = {"DICOMUpdates": {"removableAttributes": attributes}}

            self.update_image_set_metadata(
                data_store_id, image_set_id, version_id, metadata, force
            )

Caso de uso #4: volver a una versión anterior.

            metadata = {"revertToVersionId": "1"}

            self.update_image_set_metadata(
                data_store_id, image_set_id, version_id, metadata, force
            )

Cree una AWS CloudFormation pila con los recursos necesarios.

    def deploy(self):
        """
        Deploys prerequisite resources used by the scenario. The resources are
        defined in the associated `setup.yaml` AWS CloudFormation script and are deployed
        as a CloudFormation stack, so they can be easily managed and destroyed.
        """

        print("\t\tLet's deploy the stack for resource creation.")
        stack_name = q.ask("\t\tEnter a name for the stack: ", q.non_empty)

        data_store_name = q.ask(
            "\t\tEnter a name for the Health Imaging Data Store: ", q.non_empty
        )

        account_id = boto3.client("sts").get_caller_identity()["Account"]

        with open(
            "../../../../scenarios/features/healthimaging_image_sets/resources/cfn_template.yaml"
        ) as setup_file:
            setup_template = setup_file.read()
        print(f"\t\tCreating {stack_name}.")
        stack = self.cf_resource.create_stack(
            StackName=stack_name,
            TemplateBody=setup_template,
            Capabilities=["CAPABILITY_NAMED_IAM"],
            Parameters=[
                {
                    "ParameterKey": "datastoreName",
                    "ParameterValue": data_store_name,
                },
                {
                    "ParameterKey": "userAccountID",
                    "ParameterValue": account_id,
                },
            ],
        )
        print("\t\tWaiting for stack to deploy. This typically takes a minute or two.")
        waiter = self.cf_resource.meta.client.get_waiter("stack_create_complete")
        waiter.wait(StackName=stack.name)
        stack.load()
        print(f"\t\tStack status: {stack.stack_status}")

        outputs_dictionary = {
            output["OutputKey"]: output["OutputValue"] for output in stack.outputs
        }
        self.input_bucket_name = outputs_dictionary["BucketName"]
        self.output_bucket_name = outputs_dictionary["BucketName"]
        self.role_arn = outputs_dictionary["RoleArn"]
        self.data_store_id = outputs_dictionary["DatastoreID"]
        return stack

Copie los archivos DICOM en el bucket de importación de Amazon S3.

    def copy_single_object(self, key, source_bucket, target_bucket, target_directory):
        """
        Copies a single object from a source to a target bucket.

        :param key: The key of the object to copy.
        :param source_bucket: The source bucket for the copy.
        :param target_bucket: The target bucket for the copy.
        :param target_directory: The target directory for the copy.
        """
        new_key = target_directory + "/" + key
        copy_source = {"Bucket": source_bucket, "Key": key}
        self.s3_client.copy_object(
            CopySource=copy_source, Bucket=target_bucket, Key=new_key
        )
        print(f"\n\t\tCopying {key}.")

    def copy_images(
        self, source_bucket, source_directory, target_bucket, target_directory
    ):
        """
        Copies the images from the source to the target bucket using multiple threads.

        :param source_bucket: The source bucket for the images.
        :param source_directory: Directory within the source bucket.
        :param target_bucket: The target bucket for the images.
        :param target_directory: Directory within the target bucket.
        """

        # Get list of all objects in source bucket.
        list_response = self.s3_client.list_objects_v2(
            Bucket=source_bucket, Prefix=source_directory
        )
        objs = list_response["Contents"]
        keys = [obj["Key"] for obj in objs]

        # Copy the objects in the bucket.
        for key in keys:
            self.copy_single_object(key, source_bucket, target_bucket, target_directory)

        print("\t\tDone copying all objects.")

Importe los archivos DICOM en el almacén de datos de Amazon S3.

class MedicalImagingWrapper:
    """Encapsulates AWS HealthImaging functionality."""

    def __init__(self, medical_imaging_client, s3_client):
        """
        :param medical_imaging_client: A Boto3 Amazon MedicalImaging client.
        :param s3_client: A Boto3 S3 client.
        """
        self.medical_imaging_client = medical_imaging_client
        self.s3_client = s3_client

    @classmethod
    def from_client(cls):
        medical_imaging_client = boto3.client("medical-imaging")
        s3_client = boto3.client("s3")
        return cls(medical_imaging_client, s3_client)


    def start_dicom_import_job(
        self,
        data_store_id,
        input_bucket_name,
        input_directory,
        output_bucket_name,
        output_directory,
        role_arn,
    ):
        """
        Routine which starts a HealthImaging import job.

        :param data_store_id: The HealthImaging data store ID.
        :param input_bucket_name: The name of the Amazon S3 bucket containing the DICOM files.
        :param input_directory: The directory in the S3 bucket containing the DICOM files.
        :param output_bucket_name: The name of the S3 bucket for the output.
        :param output_directory: The directory in the S3 bucket to store the output.
        :param role_arn: The ARN of the IAM role with permissions for the import.
        :return: The job ID of the import.
        """

        input_uri = f"s3://{input_bucket_name}/{input_directory}/"
        output_uri = f"s3://{output_bucket_name}/{output_directory}/"
        try:
            job = self.medical_imaging_client.start_dicom_import_job(
                jobName="examplejob",
                datastoreId=data_store_id,
                dataAccessRoleArn=role_arn,
                inputS3Uri=input_uri,
                outputS3Uri=output_uri,
            )
        except ClientError as err:
            logger.error(
                "Couldn't start DICOM import job. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return job["jobId"]

Obtenga los conjuntos de imágenes que ha creado el trabajo de importación DICOM.

class MedicalImagingWrapper:
    """Encapsulates AWS HealthImaging functionality."""

    def __init__(self, medical_imaging_client, s3_client):
        """
        :param medical_imaging_client: A Boto3 Amazon MedicalImaging client.
        :param s3_client: A Boto3 S3 client.
        """
        self.medical_imaging_client = medical_imaging_client
        self.s3_client = s3_client

    @classmethod
    def from_client(cls):
        medical_imaging_client = boto3.client("medical-imaging")
        s3_client = boto3.client("s3")
        return cls(medical_imaging_client, s3_client)


    def get_image_sets_for_dicom_import_job(self, datastore_id, import_job_id):
        """
        Retrieves the image sets created for an import job.

        :param datastore_id: The HealthImaging data store ID
        :param import_job_id: The import job ID
        :return: List of image set IDs
        """

        import_job = self.medical_imaging_client.get_dicom_import_job(
            datastoreId=datastore_id, jobId=import_job_id
        )

        output_uri = import_job["jobProperties"]["outputS3Uri"]

        bucket = output_uri.split("/")[2]
        key = "/".join(output_uri.split("/")[3:])

        # Try to get the manifest.
        retries = 3
        while retries > 0:
            try:
                obj = self.s3_client.get_object(
                    Bucket=bucket, Key=key + "job-output-manifest.json"
                )
                body = obj["Body"]
                break
            except ClientError as error:
                retries = retries - 1
                time.sleep(3)
        try:
            data = json.load(body)
            expression = jmespath.compile("jobSummary.imageSetsSummary[].imageSetId")
            image_sets = expression.search(data)
        except json.decoder.JSONDecodeError as error:
            image_sets = import_job["jobProperties"]

        return image_sets


    def get_image_set(self, datastore_id, image_set_id, version_id=None):
        """
        Get the properties of an image set.

        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :param version_id: The optional version of the image set.
        :return: The image set properties.
        """
        try:
            if version_id:
                image_set = self.medical_imaging_client.get_image_set(
                    imageSetId=image_set_id,
                    datastoreId=datastore_id,
                    versionId=version_id,
                )
            else:
                image_set = self.medical_imaging_client.get_image_set(
                    imageSetId=image_set_id, datastoreId=datastore_id
                )
        except ClientError as err:
            logger.error(
                "Couldn't get image set. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return image_set

Obtenga información sobre los marcos de imágenes para los conjuntos de imágenes.

class MedicalImagingWrapper:
    """Encapsulates AWS HealthImaging functionality."""

    def __init__(self, medical_imaging_client, s3_client):
        """
        :param medical_imaging_client: A Boto3 Amazon MedicalImaging client.
        :param s3_client: A Boto3 S3 client.
        """
        self.medical_imaging_client = medical_imaging_client
        self.s3_client = s3_client

    @classmethod
    def from_client(cls):
        medical_imaging_client = boto3.client("medical-imaging")
        s3_client = boto3.client("s3")
        return cls(medical_imaging_client, s3_client)


    def get_image_frames_for_image_set(self, datastore_id, image_set_id, out_directory):
        """
        Get the image frames for an image set.

        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :param out_directory: The directory to save the file.
        :return: The image frames.
        """
        image_frames = []
        file_name = os.path.join(out_directory, f"{image_set_id}_metadata.json.gzip")
        file_name = file_name.replace("/", "\\\\")
        self.get_image_set_metadata(file_name, datastore_id, image_set_id)
        try:
            with gzip.open(file_name, "rb") as f_in:
                doc = json.load(f_in)
            instances = jmespath.search("Study.Series.*.Instances[].*[]", doc)
            for instance in instances:
                rescale_slope = jmespath.search("DICOM.RescaleSlope", instance)
                rescale_intercept = jmespath.search("DICOM.RescaleIntercept", instance)
                image_frames_json = jmespath.search("ImageFrames[][]", instance)
                for image_frame in image_frames_json:
                    checksum_json = jmespath.search(
                        "max_by(PixelDataChecksumFromBaseToFullResolution, &Width)",
                        image_frame,
                    )
                    image_frame_info = {
                        "imageSetId": image_set_id,
                        "imageFrameId": image_frame["ID"],
                        "rescaleIntercept": rescale_intercept,
                        "rescaleSlope": rescale_slope,
                        "minPixelValue": image_frame["MinPixelValue"],
                        "maxPixelValue": image_frame["MaxPixelValue"],
                        "fullResolutionChecksum": checksum_json["Checksum"],
                    }
                    image_frames.append(image_frame_info)
            return image_frames
        except TypeError:
            return {}
        except ClientError as err:
            logger.error(
                "Couldn't get image frames for image set. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        return image_frames


    def get_image_set_metadata(
        self, metadata_file, datastore_id, image_set_id, version_id=None
    ):
        """
        Get the metadata of an image set.

        :param metadata_file: The file to store the JSON gzipped metadata.
        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :param version_id: The version of the image set.
        """

        try:
            if version_id:
                image_set_metadata = self.medical_imaging_client.get_image_set_metadata(
                    imageSetId=image_set_id,
                    datastoreId=datastore_id,
                    versionId=version_id,
                )
            else:
                image_set_metadata = self.medical_imaging_client.get_image_set_metadata(
                    imageSetId=image_set_id, datastoreId=datastore_id
                )
            with open(metadata_file, "wb") as f:
                for chunk in image_set_metadata["imageSetMetadataBlob"].iter_chunks():
                    if chunk:
                        f.write(chunk)

        except ClientError as err:
            logger.error(
                "Couldn't get image metadata. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

Descarga, decodifica y verifica los marcos de imágenes.

class MedicalImagingWrapper:
    """Encapsulates AWS HealthImaging functionality."""

    def __init__(self, medical_imaging_client, s3_client):
        """
        :param medical_imaging_client: A Boto3 Amazon MedicalImaging client.
        :param s3_client: A Boto3 S3 client.
        """
        self.medical_imaging_client = medical_imaging_client
        self.s3_client = s3_client

    @classmethod
    def from_client(cls):
        medical_imaging_client = boto3.client("medical-imaging")
        s3_client = boto3.client("s3")
        return cls(medical_imaging_client, s3_client)


    def get_pixel_data(
        self, file_path_to_write, datastore_id, image_set_id, image_frame_id
    ):
        """
        Get an image frame's pixel data.

        :param file_path_to_write: The path to write the image frame's HTJ2K encoded pixel data.
        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        :param image_frame_id: The ID of the image frame.
        """
        try:
            image_frame = self.medical_imaging_client.get_image_frame(
                datastoreId=datastore_id,
                imageSetId=image_set_id,
                imageFrameInformation={"imageFrameId": image_frame_id},
            )
            with open(file_path_to_write, "wb") as f:
                for chunk in image_frame["imageFrameBlob"].iter_chunks():
                    f.write(chunk)
        except ClientError as err:
            logger.error(
                "Couldn't get image frame. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise


    def download_decode_and_check_image_frames(
        self, data_store_id, image_frames, out_directory
    ):
        """
        Downloads image frames, decodes them, and uses the checksum to validate
        the decoded images.

        :param data_store_id: The HealthImaging data store ID.
        :param image_frames: A list of dicts containing image frame information.
        :param out_directory: A directory for the downloaded images.
        :return: True if the function succeeded; otherwise, False.
        """
        total_result = True
        for image_frame in image_frames:
            image_file_path = f"{out_directory}/image_{image_frame['imageFrameId']}.jph"
            self.get_pixel_data(
                image_file_path,
                data_store_id,
                image_frame["imageSetId"],
                image_frame["imageFrameId"],
            )

            image_array = self.jph_image_to_opj_bitmap(image_file_path)
            crc32_checksum = image_frame["fullResolutionChecksum"]
            # Verify checksum.
            crc32_calculated = zlib.crc32(image_array)
            image_result = crc32_checksum == crc32_calculated
            print(
                f"\t\tImage checksum verified for {image_frame['imageFrameId']}: {image_result }"
            )
            total_result = total_result and image_result
        return total_result

    @staticmethod
    def jph_image_to_opj_bitmap(jph_file):
        """
        Decode the image to a bitmap using an OPENJPEG library.
        :param jph_file: The file to decode.
        :return: The decoded bitmap as an array.
        """
        # Use format 2 for the JPH file.
        params = openjpeg.utils.get_parameters(jph_file, 2)
        print(f"\n\t\tImage parameters for {jph_file}: \n\t\t{params}")

        image_array = openjpeg.utils.decode(jph_file, 2)

        return image_array

Eliminación de recursos.

    def destroy(self, stack):
        """
        Destroys the resources managed by the CloudFormation stack, and the CloudFormation
        stack itself.

        :param stack: The CloudFormation stack that manages the example resources.
        """

        print(f"\t\tCleaning up resources and {stack.name}.")
        data_store_id = None
        for oput in stack.outputs:
            if oput["OutputKey"] == "DatastoreID":
                data_store_id = oput["OutputValue"]
        if data_store_id is not None:
            print(f"\t\tDeleting image sets in data store {data_store_id}.")
            image_sets = self.medical_imaging_wrapper.search_image_sets(
                data_store_id, {}
            )
            image_set_ids = [image_set["imageSetId"] for image_set in image_sets]

            for image_set_id in image_set_ids:
                self.medical_imaging_wrapper.delete_image_set(
                    data_store_id, image_set_id
                )
                print(f"\t\tDeleted image set with id : {image_set_id}")

        print(f"\t\tDeleting {stack.name}.")
        stack.delete()
        print("\t\tWaiting for stack removal. This may take a few minutes.")
        waiter = self.cf_resource.meta.client.get_waiter("stack_delete_complete")
        waiter.wait(StackName=stack.name)
        print("\t\tStack delete complete.")




class MedicalImagingWrapper:
    """Encapsulates AWS HealthImaging functionality."""

    def __init__(self, medical_imaging_client, s3_client):
        """
        :param medical_imaging_client: A Boto3 Amazon MedicalImaging client.
        :param s3_client: A Boto3 S3 client.
        """
        self.medical_imaging_client = medical_imaging_client
        self.s3_client = s3_client

    @classmethod
    def from_client(cls):
        medical_imaging_client = boto3.client("medical-imaging")
        s3_client = boto3.client("s3")
        return cls(medical_imaging_client, s3_client)


    def search_image_sets(self, datastore_id, search_filter):
        """
        Search for image sets.

        :param datastore_id: The ID of the data store.
        :param search_filter: The search filter.
            For example: {"filters" : [{ "operator": "EQUAL", "values": [{"DICOMPatientId": "3524578"}]}]}.
        :return: The list of image sets.
        """
        try:
            paginator = self.medical_imaging_client.get_paginator("search_image_sets")
            page_iterator = paginator.paginate(
                datastoreId=datastore_id, searchCriteria=search_filter
            )
            metadata_summaries = []
            for page in page_iterator:
                metadata_summaries.extend(page["imageSetsMetadataSummaries"])
        except ClientError as err:
            logger.error(
                "Couldn't search image sets. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return metadata_summaries


    def delete_image_set(self, datastore_id, image_set_id):
        """
        Delete an image set.

        :param datastore_id: The ID of the data store.
        :param image_set_id: The ID of the image set.
        """
        try:
            delete_results = self.medical_imaging_client.delete_image_set(
                imageSetId=image_set_id, datastoreId=datastore_id
            )
        except ClientError as err:
            logger.error(
                "Couldn't delete image set. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

Para etiquetar un almacén de datos

    a_data_store_arn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012"

    medical_imaging_wrapper.tag_resource(data_store_arn, {"Deployment": "Development"})

Función de utilidad para etiquetar un recurso.

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def tag_resource(self, resource_arn, tags):
        """
        Tag a resource.

        :param resource_arn: The ARN of the resource.
        :param tags: The tags to apply.
        """
        try:
            self.health_imaging_client.tag_resource(resourceArn=resource_arn, tags=tags)
        except ClientError as err:
            logger.error(
                "Couldn't tag resource. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

Para enumerar las etiquetas de almacenes de datos

    a_data_store_arn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012"

    medical_imaging_wrapper.list_tags_for_resource(data_store_arn)

La función de utilidad para enumerar las etiquetas de un recurso.

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def list_tags_for_resource(self, resource_arn):
        """
        List the tags for a resource.

        :param resource_arn: The ARN of the resource.
        :return: The list of tags.
        """
        try:
            tags = self.health_imaging_client.list_tags_for_resource(
                resourceArn=resource_arn
            )
        except ClientError as err:
            logger.error(
                "Couldn't list tags for resource. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return tags["tags"]

Para desetiquetar un almacén de datos

    a_data_store_arn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012"

    medical_imaging_wrapper.untag_resource(data_store_arn, ["Deployment"])

La función de utilidad para eliminar la etiqueta de un recurso.

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def untag_resource(self, resource_arn, tag_keys):
        """
        Untag a resource.

        :param resource_arn: The ARN of the resource.
        :param tag_keys: The tag keys to remove.
        """
        try:
            self.health_imaging_client.untag_resource(
                resourceArn=resource_arn, tagKeys=tag_keys
            )
        except ClientError as err:
            logger.error(
                "Couldn't untag resource. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

El código siguiente crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)

Para etiquetar un conjunto de imágenes

    an_image_set_arn = (
        "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012/"
        "imageset/12345678901234567890123456789012"
    )

    medical_imaging_wrapper.tag_resource(image_set_arn, {"Deployment": "Development"})

Función de utilidad para etiquetar un recurso.

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def tag_resource(self, resource_arn, tags):
        """
        Tag a resource.

        :param resource_arn: The ARN of the resource.
        :param tags: The tags to apply.
        """
        try:
            self.health_imaging_client.tag_resource(resourceArn=resource_arn, tags=tags)
        except ClientError as err:
            logger.error(
                "Couldn't tag resource. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

Para enumerar las etiquetas de un conjunto de imágenes

    an_image_set_arn = (
        "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012/"
        "imageset/12345678901234567890123456789012"
    )

    medical_imaging_wrapper.list_tags_for_resource(image_set_arn)

La función de utilidad para enumerar las etiquetas de un recurso.

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def list_tags_for_resource(self, resource_arn):
        """
        List the tags for a resource.

        :param resource_arn: The ARN of the resource.
        :return: The list of tags.
        """
        try:
            tags = self.health_imaging_client.list_tags_for_resource(
                resourceArn=resource_arn
            )
        except ClientError as err:
            logger.error(
                "Couldn't list tags for resource. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return tags["tags"]

Para desetiquetar un conjunto de imágenes

    an_image_set_arn = (
        "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012/"
        "imageset/12345678901234567890123456789012"
    )

    medical_imaging_wrapper.untag_resource(image_set_arn, ["Deployment"])

La función de utilidad para eliminar la etiqueta de un recurso.

class MedicalImagingWrapper:
    def __init__(self, health_imaging_client):
        self.health_imaging_client = health_imaging_client


    def untag_resource(self, resource_arn, tag_keys):
        """
        Untag a resource.

        :param resource_arn: The ARN of the resource.
        :param tag_keys: The tag keys to remove.
        """
        try:
            self.health_imaging_client.untag_resource(
                resourceArn=resource_arn, tagKeys=tag_keys
            )
        except ClientError as err:
            logger.error(
                "Couldn't untag resource. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

El código siguiente crea una instancia del MedicalImagingWrapper objeto.

    client = boto3.client("medical-imaging")
    medical_imaging_wrapper = MedicalImagingWrapper(client)