Sono disponibili altri esempi AWS SDK nel repository [AWS Doc SDK](https://github.com/awsdocs/aws-doc-sdk-examples) Examples. GitHub
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# HealthImaging esempi che utilizzano SDK per Python (Boto3)
I seguenti esempi di codice mostrano come eseguire azioni e implementare scenari comuni utilizzando AWS SDK per Python (Boto3) with HealthImaging.
Le *azioni* sono estratti di codice da programmi più grandi e devono essere eseguite nel contesto. Sebbene le azioni mostrino come richiamare le singole funzioni del servizio, è possibile visualizzarle contestualizzate negli scenari correlati.
*Scenari*: esempi di codice che mostrano come eseguire un’attività specifica chiamando più funzioni all’interno dello stesso servizio o combinate con altri Servizi AWS.
Ogni esempio include un link al codice sorgente completo, in cui vengono fornite le istruzioni su come configurare ed eseguire il codice nel contesto.
**Topics**
+ [Nozioni di base](#get_started)
+ [Azioni](#actions)
+ [Scenari](#scenarios)
## Nozioni di base
### Salve HealthImaging
L’esempio di codice seguente mostra come iniziare a utilizzare HealthImaging.
**SDK per 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"))
```
+ Per i dettagli sull'API, consulta [ListDatastores AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/ListDatastores)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging/imaging_set_and_frames_workflow#code-examples).
## Azioni
### `CopyImageSet`
Il seguente esempio di codice mostra come usare`CopyImageSet`.
**SDK per Python (Boto3)**
Funzione di utilità per copiare un set di immagini.
```
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"]
```
Copia un set di immagini senza una destinazione.
```
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,
)
```
Copia un set di immagini con una destinazione.
```
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 sottoinsieme di un set di immagini.
```
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,
)
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [CopyImageSet AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/CopyImageSet)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `CreateDatastore`
Il seguente esempio di codice mostra come usare`CreateDatastore`.
**SDK per Python (Boto3)**
```
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"]
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [CreateDatastore AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/CreateDatastore)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `DeleteDatastore`
Il seguente esempio di codice mostra come usare`DeleteDatastore`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [DeleteDatastore AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/DeleteDatastore)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `DeleteImageSet`
Il seguente esempio di codice mostra come usare`DeleteImageSet`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [DeleteImageSet AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/DeleteImageSet)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `GetDICOMImportJob`
Il seguente esempio di codice mostra come usare`GetDICOMImportJob`.
**SDK per Python (Boto3)**
```
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"]
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [Get DICOMImport Job](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/GetDICOMImportJob) in *AWS SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `GetDatastore`
Il seguente esempio di codice mostra come usare`GetDatastore`.
**SDK per Python (Boto3)**
```
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"]
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [GetDatastore AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/GetDatastore)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `GetImageFrame`
Il seguente esempio di codice mostra come usare`GetImageFrame`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [GetImageFrame AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/GetImageFrame)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `GetImageSet`
Il seguente esempio di codice mostra come usare`GetImageSet`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [GetImageSet AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/GetImageSet)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `GetImageSetMetadata`
Il seguente esempio di codice mostra come usare`GetImageSetMetadata`.
**SDK per Python (Boto3)**
Funzione di utilità per ottenere i metadati del set di immagini.
```
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
```
Ottiene i metadati del set di immagini senza la versione.
```
image_set_metadata = self.health_imaging_client.get_image_set_metadata(
imageSetId=image_set_id, datastoreId=datastore_id
)
```
Ottiene i metadati del set di immagini con la versione.
```
image_set_metadata = self.health_imaging_client.get_image_set_metadata(
imageSetId=image_set_id,
datastoreId=datastore_id,
versionId=version_id,
)
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [GetImageSetMetadata AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/GetImageSetMetadata)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `ListDICOMImportJobs`
Il seguente esempio di codice mostra come usare`ListDICOMImportJobs`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [List DICOMImport Jobs](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/ListDICOMImportJobs) in *AWS SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `ListDatastores`
Il seguente esempio di codice mostra come usare`ListDatastores`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [ListDatastores AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/ListDatastores)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `ListImageSetVersions`
Il seguente esempio di codice mostra come usare`ListImageSetVersions`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [ListImageSetVersions AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/ListImageSetVersions)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `ListTagsForResource`
Il seguente esempio di codice mostra come usare`ListTagsForResource`.
**SDK per Python (Boto3)**
```
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"]
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [ListTagsForResource AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/ListTagsForResource)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `SearchImageSets`
Il seguente esempio di codice mostra come usare`SearchImageSets`.
**SDK per Python (Boto3)**
La funzione di utilità per la ricerca di set di immagini.
```
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 d’uso 1: operatore EQUAL.
```
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 d'uso \$12: operatore BETWEEN che utilizza DICOMStudy data e DICOMStudy ora.
```
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 d’uso 3: operatore BETWEEN con createdAt. Gli studi relativi agli orari sono stati precedentemente resi persistenti.
```
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 d'uso \$14: operatore EQUAL su DICOMSeries instanceUID e BETWEEN su updatedAt e ordina la risposta in ordine ASC nel 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}")
```
Il codice seguente crea un'istanza dell'oggetto. MedicalImagingWrapper
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [SearchImageSets AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/SearchImageSets)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `StartDICOMImportJob`
Il seguente esempio di codice mostra come usare`StartDICOMImportJob`.
**SDK per Python (Boto3)**
```
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"]
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [Start DICOMImport Job](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/StartDICOMImportJob) in *AWS SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `TagResource`
Il seguente esempio di codice mostra come usare`TagResource`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [TagResource AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/TagResource)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `UntagResource`
Il seguente esempio di codice mostra come usare`UntagResource`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per i dettagli sull'API, consulta [UntagResource AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/UntagResource)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
### `UpdateImageSetMetadata`
Il seguente esempio di codice mostra come usare`UpdateImageSetMetadata`.
**SDK per Python (Boto3)**
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
Caso d’uso 1: inserisce o aggiorna un attributo.
```
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 d’uso 2: rimuove un attributo.
```
# 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 d’uso 3: rimuove un’istanza.
```
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 d’uso 4: ripristina una versione precedente.
```
metadata = {"revertToVersionId": "1"}
self.update_image_set_metadata(
data_store_id, image_set_id, version_id, metadata, force
)
```
+ Per i dettagli sull'API, consulta [UpdateImageSetMetadata AWS](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/UpdateImageSetMetadata)*SDK for Python (Boto3) API Reference*.
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging#code-examples).
## Scenari
### Nozioni di base su set di immagini e frame di immagini
Il seguente esempio di codice mostra come importare file DICOM e scaricare cornici di immagini. HealthImaging
L’implementazione è strutturata come un’applicazione della riga di comando.
+ Impostare le risorse per l’importazione DICOM.
+ Importare file DICOM in un datastore.
+ Recuperate il set di immagini IDs per il processo di importazione.
+ Recuperate la cornice dell'immagine IDs per i set di immagini.
+ Scaricare, decodificare e verifica i frame di immagini.
+ Eliminare le risorse.
**SDK per Python (Boto3)**
Crea una CloudFormation pila con le risorse necessarie.
```
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
```
Copiare file DICOM nel bucket di importazione di 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.")
```
Importare file DICOM nel datastore 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"]
```
Ottiene set di immagini creati dal processo di importazione 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
```
Ottiene le informazioni sui frame di immagini per i set di immagini.
```
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
```
Scarica, decodifica e verifica i frame di immagini.
```
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
```
Eliminare le risorse.
```
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
```
+ Per informazioni dettagliate sull’API, consulta i seguenti argomenti nella *documentazione di riferimento dell’API AWS SDK per Python (Boto3)*.
+ [DeleteImageSet](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/DeleteImageSet)
+ [Trova un DICOMImport lavoro](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/GetDICOMImportJob)
+ [GetImageFrame](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/GetImageFrame)
+ [GetImageSetMetadata](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/GetImageSetMetadata)
+ [SearchImageSets](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/SearchImageSets)
+ [Avvia DICOMImport Job](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/StartDICOMImportJob)
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/medical-imaging/imaging_set_and_frames_workflow#code-examples).
### Tagging di un datastore
Il seguente esempio di codice mostra come etichettare un archivio HealthImaging dati.
**SDK per Python (Boto3)**
Come taggare un datastore.
```
a_data_store_arn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012"
medical_imaging_wrapper.tag_resource(data_store_arn, {"Deployment": "Development"})
```
La funzione di utilità per taggare una risorsa.
```
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
```
Come elencare i tag di un datastore.
```
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 funzione di utilità per elencare i tag di una risorsa.
```
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"]
```
Come rimuovere i tag di un datastore.
```
a_data_store_arn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012"
medical_imaging_wrapper.untag_resource(data_store_arn, ["Deployment"])
```
La funzione di utilità per rimuovere i tag di una risorsa.
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per informazioni dettagliate sull’API, consulta i seguenti argomenti nella *documentazione di riferimento dell’API AWS SDK per Python (Boto3)*.
+ [ListTagsForResource](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/ListTagsForResource)
+ [TagResource](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/TagResource)
+ [UntagResource](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/UntagResource)
C'è altro da fare. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javascriptv3/example_code/medical-imaging#code-examples).
### Tagging un set di immagini
Il seguente esempio di codice mostra come etichettare un set di HealthImaging immagini.
**SDK per Python (Boto3)**
Come taggare un set di immagini.
```
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"})
```
La funzione di utilità per taggare una risorsa.
```
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
```
Come elencare i tag di un set di immagini.
```
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 funzione di utilità per elencare i tag di una risorsa.
```
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"]
```
Come rimuovere i tag da un set di immagini.
```
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 funzione di utilità per rimuovere i tag di una risorsa.
```
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
```
Il codice seguente crea un'istanza dell' MedicalImagingWrapper oggetto.
```
client = boto3.client("medical-imaging")
medical_imaging_wrapper = MedicalImagingWrapper(client)
```
+ Per informazioni dettagliate sull’API, consulta i seguenti argomenti nella *documentazione di riferimento dell’API AWS SDK per Python (Boto3)*.
+ [ListTagsForResource](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/ListTagsForResource)
+ [TagResource](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/TagResource)
+ [UntagResource](https://docs.aws.amazon.com/goto/boto3/medical-imaging-2023-07-19/UntagResource)
C'è altro da fare. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javascriptv3/example_code/medical-imaging#code-examples).