取得影像集中繼資料

取得影像集中繼資料的公用程式函數。

//! Routine which gets a HealthImaging image set's metadata.
/*!
  \param dataStoreID: The HealthImaging data store ID.
  \param imageSetID: The HealthImaging image set ID.
  \param versionID: The HealthImaging image set version ID, ignored if empty.
  \param outputFilePath: The path where the metadata will be stored as gzipped json.
  \param clientConfig: Aws client configuration.
  \\return bool: Function succeeded.
*/
bool AwsDoc::Medical_Imaging::getImageSetMetadata(const Aws::String &dataStoreID,
                                                  const Aws::String &imageSetID,
                                                  const Aws::String &versionID,
                                                  const Aws::String &outputFilePath,
                                                  const Aws::Client::ClientConfiguration &clientConfig) {
    Aws::MedicalImaging::Model::GetImageSetMetadataRequest request;
    request.SetDatastoreId(dataStoreID);
    request.SetImageSetId(imageSetID);
    if (!versionID.empty()) {
        request.SetVersionId(versionID);
    }
    Aws::MedicalImaging::MedicalImagingClient client(clientConfig);
    Aws::MedicalImaging::Model::GetImageSetMetadataOutcome outcome = client.GetImageSetMetadata(
            request);
    if (outcome.IsSuccess()) {
        std::ofstream file(outputFilePath, std::ios::binary);
        auto &metadata = outcome.GetResult().GetImageSetMetadataBlob();
        file << metadata.rdbuf();
    }
    else {
        std::cerr << "Failed to get image set metadata: "
                  << outcome.GetError().GetMessage() << std::endl;
    }

    return outcome.IsSuccess();
}

取得不含版本的影像集中繼資料。

        if (AwsDoc::Medical_Imaging::getImageSetMetadata(dataStoreID, imageSetID, "", outputFilePath, clientConfig))
        {
            std::cout << "Successfully retrieved image set metadata." << std::endl;
            std::cout << "Metadata stored in: " << outputFilePath << std::endl;
        }

取得含版本的影像集中繼資料。

        if (AwsDoc::Medical_Imaging::getImageSetMetadata(dataStoreID, imageSetID, versionID, outputFilePath, clientConfig))
        {
            std::cout << "Successfully retrieved image set metadata." << std::endl;
            std::cout << "Metadata stored in: " << outputFilePath << std::endl;
        }

範例 1：取得不含版本的影像集中繼資料

下列 get-image-set-metadata 程式碼範例會取得影像集的中繼資料，而不指定版本。

注意：outfile 為必要參數

aws medical-imaging get-image-set-metadata \
    --datastore-id 12345678901234567890123456789012 \
    --image-set-id ea92b0d8838c72a3f25d00d13616f87e \
    studymetadata.json.gz

傳回的中繼資料會以 gzip 壓縮，並存放在 studymetadata.json.gz 檔案中。若要檢視傳回 JSON 物件的內容，您必須先解壓縮它。

輸出：

{
    "contentType": "application/json",
    "contentEncoding": "gzip"
}

範例 2：使用版本取得影像集中繼資料

下列 get-image-set-metadata 程式碼範例會取得具有指定版本之影像集的中繼資料。

注意：outfile 為必要參數

aws medical-imaging get-image-set-metadata \
    --datastore-id 12345678901234567890123456789012 \
    --image-set-id ea92b0d8838c72a3f25d00d13616f87e \
    --version-id 1 \
    studymetadata.json.gz

傳回的中繼資料會以 gzip 壓縮，並存放在 studymetadata.json.gz 檔案中。若要檢視傳回 JSON 物件的內容，您必須先解壓縮它。

輸出：

{
    "contentType": "application/json",
    "contentEncoding": "gzip"
}

如需詳細資訊，請參閱《AWS HealthImaging 開發人員指南》中的取得影像集中繼資料。

    public static void getMedicalImageSetMetadata(MedicalImagingClient medicalImagingClient,
            String destinationPath,
            String datastoreId,
            String imagesetId,
            String versionId) {

        try {
            GetImageSetMetadataRequest.Builder getImageSetMetadataRequestBuilder = GetImageSetMetadataRequest.builder()
                    .datastoreId(datastoreId)
                    .imageSetId(imagesetId);

            if (versionId != null) {
                getImageSetMetadataRequestBuilder = getImageSetMetadataRequestBuilder.versionId(versionId);
            }

            medicalImagingClient.getImageSetMetadata(getImageSetMetadataRequestBuilder.build(),
                    FileSystems.getDefault().getPath(destinationPath));

            System.out.println("Metadata downloaded to " + destinationPath);
        } catch (MedicalImagingException e) {
            System.err.println(e.awsErrorDetails().errorMessage());
            System.exit(1);
        }
    }

取得影像集中繼資料的公用程式函數。

import { GetImageSetMetadataCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";
import { writeFileSync } from "node:fs";

/**
 * @param {string} metadataFileName - The name of the file for the gzipped metadata.
 * @param {string} datastoreId - The ID of the data store.
 * @param {string} imagesetId - The ID of the image set.
 * @param {string} versionID - The optional version ID of the image set.
 */
export const getImageSetMetadata = async (
  metadataFileName = "metadata.json.gzip",
  datastoreId = "xxxxxxxxxxxxxx",
  imagesetId = "xxxxxxxxxxxxxx",
  versionID = "",
) => {
  const params = { datastoreId: datastoreId, imageSetId: imagesetId };

  if (versionID) {
    params.versionID = versionID;
  }

  const response = await medicalImagingClient.send(
    new GetImageSetMetadataCommand(params),
  );
  const buffer = await response.imageSetMetadataBlob.transformToByteArray();
  writeFileSync(metadataFileName, buffer);

  console.log(response);
  // {
  //     '$metadata': {
  //     httpStatusCode: 200,
  //         requestId: '5219b274-30ff-4986-8cab-48753de3a599',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  // },
  //     contentType: 'application/json',
  //     contentEncoding: 'gzip',
  //     imageSetMetadataBlob: <ref *1> IncomingMessage {}
  // }

  return response;
};

取得不含版本的影像集中繼資料。

  try {
    await getImageSetMetadata(
      "metadata.json.gzip",
      "12345678901234567890123456789012",
      "12345678901234567890123456789012",
    );
  } catch (err) {
    console.log("Error", err);
  }

取得含版本的影像集中繼資料。

  try {
    await getImageSetMetadata(
      "metadata2.json.gzip",
      "12345678901234567890123456789012",
      "12345678901234567890123456789012",
      "1",
    );
  } catch (err) {
    console.log("Error", err);
  }

取得影像集中繼資料的公用程式函數。

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

取得不含版本的影像集中繼資料。

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

取得含版本的影像集中繼資料。

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

下列程式碼會執行個體化 MedicalImagingWrapper 物件。

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