HealthImaging 使用适用于 JavaScript (v3) 的 SDK 的示例

import {
  ListDatastoresCommand,
  MedicalImagingClient,
} from "@aws-sdk/client-medical-imaging";

// When no region or credentials are provided, the SDK will use the
// region and credentials from the local AWS config.
const client = new MedicalImagingClient({});

export const helloMedicalImaging = async () => {
  const command = new ListDatastoresCommand({});

  const { datastoreSummaries } = await client.send(command);
  console.log("Datastores: ");
  console.log(datastoreSummaries.map((item) => item.datastoreName).join("\n"));
  return datastoreSummaries;
};

用于复制映像集的实用程序函数。

import { CopyImageSetCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreId - The ID of the data store.
 * @param {string} imageSetId - The source image set ID.
 * @param {string} sourceVersionId - The source version ID.
 * @param {string} destinationImageSetId - The optional ID of the destination image set.
 * @param {string} destinationVersionId - The optional version ID of the destination image set.
 * @param {boolean} force - Force the copy action.
 * @param {[string]} copySubsets - A subset of instance IDs to copy.
 */
export const copyImageSet = async (
  datastoreId = "xxxxxxxxxxx",
  imageSetId = "xxxxxxxxxxxx",
  sourceVersionId = "1",
  destinationImageSetId = "",
  destinationVersionId = "",
  force = false,
  copySubsets = [],
) => {
  try {
    const params = {
      datastoreId: datastoreId,
      sourceImageSetId: imageSetId,
      copyImageSetInformation: {
        sourceImageSet: { latestVersionId: sourceVersionId },
      },
      force: force,
    };
    if (destinationImageSetId !== "" && destinationVersionId !== "") {
      params.copyImageSetInformation.destinationImageSet = {
        imageSetId: destinationImageSetId,
        latestVersionId: destinationVersionId,
      };
    }

    if (copySubsets.length > 0) {
      let copySubsetsJson;
      copySubsetsJson = {
        SchemaVersion: 1.1,
        Study: {
          Series: {
            imageSetId: {
              Instances: {},
            },
          },
        },
      };

      for (let i = 0; i < copySubsets.length; i++) {
        copySubsetsJson.Study.Series.imageSetId.Instances[copySubsets[i]] = {};
      }

      params.copyImageSetInformation.dicomCopies = copySubsetsJson;
    }

    const response = await medicalImagingClient.send(
      new CopyImageSetCommand(params),
    );
    console.log(response);
    // {
    //     '$metadata': {
    //         httpStatusCode: 200,
    //         requestId: 'd9b219ce-cc48-4a44-a5b2-c5c3068f1ee8',
    //         extendedRequestId: undefined,
    //         cfId: undefined,
    //         attempts: 1,
    //         totalRetryDelay: 0
    //      },
    //       datastoreId: 'xxxxxxxxxxxxxx',
    //       destinationImageSetProperties: {
    //             createdAt: 2023-09-27T19:46:21.824Z,
    //             imageSetArn: 'arn:aws:medical-imaging:us-east-1:xxxxxxxxxxx:datastore/xxxxxxxxxxxxx/imageset/xxxxxxxxxxxxxxxxxxx',
    //             imageSetId: 'xxxxxxxxxxxxxxx',
    //             imageSetState: 'LOCKED',
    //             imageSetWorkflowStatus: 'COPYING',
    //             latestVersionId: '1',
    //             updatedAt: 2023-09-27T19:46:21.824Z
    //       },
    //       sourceImageSetProperties: {
    //             createdAt: 2023-09-22T14:49:26.427Z,
    //             imageSetArn: 'arn:aws:medical-imaging:us-east-1:xxxxxxxxxxx:datastore/xxxxxxxxxxxxx/imageset/xxxxxxxxxxxxxxxx',
    //             imageSetId: 'xxxxxxxxxxxxxxxx',
    //             imageSetState: 'LOCKED',
    //             imageSetWorkflowStatus: 'COPYING_WITH_READ_ONLY_ACCESS',
    //             latestVersionId: '4',
    //             updatedAt: 2023-09-27T19:46:21.824Z
    //      }
    // }
    return response;
  } catch (err) {
    console.error(err);
  }
};

复制没有目标的映像集。

  await copyImageSet(
    "12345678901234567890123456789012",
    "12345678901234567890123456789012",
    "1",
  );

复制带有目标的映像集。

  await copyImageSet(
    "12345678901234567890123456789012",
    "12345678901234567890123456789012",
    "1",
    "12345678901234567890123456789012",
    "1",
    false,
  );

复制带有目标的影像集的子集并强制复制。

  await copyImageSet(
    "12345678901234567890123456789012",
    "12345678901234567890123456789012",
    "1",
    "12345678901234567890123456789012",
    "1",
    true,
    ["12345678901234567890123456789012", "11223344556677889900112233445566"],
  );

import { CreateDatastoreCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreName - The name of the data store to create.
 */
export const createDatastore = async (datastoreName = "DATASTORE_NAME") => {
  const response = await medicalImagingClient.send(
    new CreateDatastoreCommand({ datastoreName: datastoreName }),
  );
  console.log(response);
  // {
  //   '$metadata': {
  //       httpStatusCode: 200,
  //       requestId: 'a71cd65f-2382-49bf-b682-f9209d8d399b',
  //       extendedRequestId: undefined,
  //       cfId: undefined,
  //       attempts: 1,
  //       totalRetryDelay: 0
  //    },
  //    datastoreId: 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
  //    datastoreStatus: 'CREATING'
  // }
  return response;
};

import { DeleteDatastoreCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreId - The ID of the data store to delete.
 */
export const deleteDatastore = async (datastoreId = "DATASTORE_ID") => {
  const response = await medicalImagingClient.send(
    new DeleteDatastoreCommand({ datastoreId }),
  );
  console.log(response);
  // {
  //   '$metadata': {
  //           httpStatusCode: 200,
  //           requestId: 'f5beb409-678d-48c9-9173-9a001ee1ebb1',
  //           extendedRequestId: undefined,
  //           cfId: undefined,
  //           attempts: 1,
  //           totalRetryDelay: 0
  //        },
  //     datastoreId: 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
  //     datastoreStatus: 'DELETING'
  // }

  return response;
};

import { DeleteImageSetCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreId - The data store ID.
 * @param {string} imageSetId - The image set ID.
 */
export const deleteImageSet = async (
  datastoreId = "xxxxxxxxxxxxxxxx",
  imageSetId = "xxxxxxxxxxxxxxxx",
) => {
  const response = await medicalImagingClient.send(
    new DeleteImageSetCommand({
      datastoreId: datastoreId,
      imageSetId: imageSetId,
    }),
  );
  console.log(response);
  // {
  //    '$metadata': {
  //         httpStatusCode: 200,
  //         requestId: '6267bbd2-eaa5-4a50-8ee8-8fddf535cf73',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  //     },
  //     datastoreId: 'xxxxxxxxxxxxxxxx',
  //     imageSetId: 'xxxxxxxxxxxxxxx',
  //     imageSetState: 'LOCKED',
  //     imageSetWorkflowStatus: 'DELETING'
  // }
  return response;
};

import { GetDICOMImportJobCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreId - The ID of the data store.
 * @param {string} jobId - The ID of the import job.
 */
export const getDICOMImportJob = async (
  datastoreId = "xxxxxxxxxxxxxxxxxxxx",
  jobId = "xxxxxxxxxxxxxxxxxxxx",
) => {
  const response = await medicalImagingClient.send(
    new GetDICOMImportJobCommand({ datastoreId: datastoreId, jobId: jobId }),
  );
  console.log(response);
  // {
  //     '$metadata': {
  //     httpStatusCode: 200,
  //         requestId: 'a2637936-78ea-44e7-98b8-7a87d95dfaee',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  // },
  //     jobProperties: {
  //         dataAccessRoleArn: 'arn:aws:iam::xxxxxxxxxxxx:role/dicom_import',
  //             datastoreId: 'xxxxxxxxxxxxxxxxxxxxxxxxx',
  //             endedAt: 2023-09-19T17:29:21.753Z,
  //             inputS3Uri: 's3://healthimaging-source/CTStudy/',
  //             jobId: ''xxxxxxxxxxxxxxxxxxxxxxxxx'',
  //             jobName: 'job_1',
  //             jobStatus: 'COMPLETED',
  //             outputS3Uri: 's3://health-imaging-dest/ouput_ct/'xxxxxxxxxxxxxxxxxxxxxxxxx'-DicomImport-'xxxxxxxxxxxxxxxxxxxxxxxxx'/',
  //             submittedAt: 2023-09-19T17:27:25.143Z
  //     }
  // }

  return response;
};

import { GetDatastoreCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreID - The ID of the data store.
 */
export const getDatastore = async (datastoreID = "DATASTORE_ID") => {
  const response = await medicalImagingClient.send(
    new GetDatastoreCommand({ datastoreId: datastoreID }),
  );
  console.log(response);
  // {
  //   '$metadata': {
  //       httpStatusCode: 200,
  //       requestId: '55ea7d2e-222c-4a6a-871e-4f591f40cadb',
  //       extendedRequestId: undefined,
  //       cfId: undefined,
  //       attempts: 1,
  //       totalRetryDelay: 0
  //    },
  //   datastoreProperties: {
  //        createdAt: 2023-08-04T18:50:36.239Z,
  //         datastoreArn: 'arn:aws:medical-imaging:us-east-1:xxxxxxxxx:datastore/xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
  //         datastoreId: 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
  //         datastoreName: 'my_datastore',
  //         datastoreStatus: 'ACTIVE',
  //         updatedAt: 2023-08-04T18:50:36.239Z
  //   }
  // }
  return response.datastoreProperties;
};

import { GetImageFrameCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} imageFrameFileName - The name of the file for the HTJ2K-encoded image frame.
 * @param {string} datastoreID - The data store's ID.
 * @param {string} imageSetID - The image set's ID.
 * @param {string} imageFrameID - The image frame's ID.
 */
export const getImageFrame = async (
  imageFrameFileName = "image.jph",
  datastoreID = "DATASTORE_ID",
  imageSetID = "IMAGE_SET_ID",
  imageFrameID = "IMAGE_FRAME_ID",
) => {
  const response = await medicalImagingClient.send(
    new GetImageFrameCommand({
      datastoreId: datastoreID,
      imageSetId: imageSetID,
      imageFrameInformation: { imageFrameId: imageFrameID },
    }),
  );
  const buffer = await response.imageFrameBlob.transformToByteArray();
  writeFileSync(imageFrameFileName, buffer);

  console.log(response);
  // {
  //     '$metadata': {
  //         httpStatusCode: 200,
  //         requestId: 'e4ab42a5-25a3-4377-873f-374ecf4380e1',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  //     },
  //     contentType: 'application/octet-stream',
  //     imageFrameBlob: <ref *1> IncomingMessage {}
  // }
  return response;
};

import { GetImageSetCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreId - The ID of the data store.
 * @param {string} imageSetId - The ID of the image set.
 * @param {string} imageSetVersion - The optional version of the image set.
 *
 */
export const getImageSet = async (
  datastoreId = "xxxxxxxxxxxxxxx",
  imageSetId = "xxxxxxxxxxxxxxx",
  imageSetVersion = "",
) => {
  const params = { datastoreId: datastoreId, imageSetId: imageSetId };
  if (imageSetVersion !== "") {
    params.imageSetVersion = imageSetVersion;
  }
  const response = await medicalImagingClient.send(
    new GetImageSetCommand(params),
  );
  console.log(response);
  // {
  //     '$metadata': {
  //     httpStatusCode: 200,
  //         requestId: '0615c161-410d-4d06-9d8c-6e1241bb0a5a',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  // },
  //     createdAt: 2023-09-22T14:49:26.427Z,
  //     datastoreId: 'xxxxxxxxxxxxxxx',
  //     imageSetArn: 'arn:aws:medical-imaging:us-east-1:xxxxxxxxxx:datastore/xxxxxxxxxxxxxxxxxxxx/imageset/xxxxxxxxxxxxxxxxxxxx',
  //     imageSetId: 'xxxxxxxxxxxxxxx',
  //     imageSetState: 'ACTIVE',
  //     imageSetWorkflowStatus: 'CREATED',
  //     updatedAt: 2023-09-22T14:49:26.427Z,
  //     versionId: '1'
  // }

  return response;
};

用于获取映像集元数据的实用程序函数。

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;
};

获取没有版本的映像集元数据。

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

获取带有版本的映像集元数据。

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

import { paginateListDICOMImportJobs } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreId - The ID of the data store.
 */
export const listDICOMImportJobs = async (
  datastoreId = "xxxxxxxxxxxxxxxxxx",
) => {
  const paginatorConfig = {
    client: medicalImagingClient,
    pageSize: 50,
  };

  const commandParams = { datastoreId: datastoreId };
  const paginator = paginateListDICOMImportJobs(paginatorConfig, commandParams);

  const jobSummaries = [];
  for await (const page of paginator) {
    // Each page contains a list of `jobSummaries`. The list is truncated if is larger than `pageSize`.
    jobSummaries.push(...page.jobSummaries);
    console.log(page);
  }
  // {
  //     '$metadata': {
  //     httpStatusCode: 200,
  //         requestId: '3c20c66e-0797-446a-a1d8-91b742fd15a0',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  // },
  //     jobSummaries: [
  //         {
  //             dataAccessRoleArn: 'arn:aws:iam::xxxxxxxxxxxx:role/dicom_import',
  //             datastoreId: 'xxxxxxxxxxxxxxxxxxxxxxxxx',
  //             endedAt: 2023-09-22T14:49:51.351Z,
  //             jobId: 'xxxxxxxxxxxxxxxxxxxxxxxxx',
  //             jobName: 'test-1',
  //             jobStatus: 'COMPLETED',
  //             submittedAt: 2023-09-22T14:48:45.767Z
  // }
  // ]}

  return jobSummaries;
};

import { paginateListDatastores } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

export const listDatastores = async () => {
  const paginatorConfig = {
    client: medicalImagingClient,
    pageSize: 50,
  };

  const commandParams = {};
  const paginator = paginateListDatastores(paginatorConfig, commandParams);

  /**
   * @type {import("@aws-sdk/client-medical-imaging").DatastoreSummary[]}
   */
  const datastoreSummaries = [];
  for await (const page of paginator) {
    // Each page contains a list of `jobSummaries`. The list is truncated if is larger than `pageSize`.
    datastoreSummaries.push(...page.datastoreSummaries);
    console.log(page);
  }
  // {
  //   '$metadata': {
  //       httpStatusCode: 200,
  //       requestId: '6aa99231-d9c2-4716-a46e-edb830116fa3',
  //       extendedRequestId: undefined,
  //       cfId: undefined,
  //       attempts: 1,
  //       totalRetryDelay: 0
  //   },
  //   datastoreSummaries: [
  //     {
  //       createdAt: 2023-08-04T18:49:54.429Z,
  //       datastoreArn: 'arn:aws:medical-imaging:us-east-1:xxxxxxxxx:datastore/xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
  //       datastoreId: 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
  //       datastoreName: 'my_datastore',
  //       datastoreStatus: 'ACTIVE',
  //       updatedAt: 2023-08-04T18:49:54.429Z
  //     }
  //     ...
  //   ]
  // }

  return datastoreSummaries;
};

import { paginateListImageSetVersions } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreId - The ID of the data store.
 * @param {string} imageSetId - The ID of the image set.
 */
export const listImageSetVersions = async (
  datastoreId = "xxxxxxxxxxxx",
  imageSetId = "xxxxxxxxxxxx",
) => {
  const paginatorConfig = {
    client: medicalImagingClient,
    pageSize: 50,
  };

  const commandParams = { datastoreId, imageSetId };
  const paginator = paginateListImageSetVersions(
    paginatorConfig,
    commandParams,
  );

  const imageSetPropertiesList = [];
  for await (const page of paginator) {
    // Each page contains a list of `jobSummaries`. The list is truncated if is larger than `pageSize`.
    imageSetPropertiesList.push(...page.imageSetPropertiesList);
    console.log(page);
  }
  // {
  //     '$metadata': {
  //         httpStatusCode: 200,
  //         requestId: '74590b37-a002-4827-83f2-3c590279c742',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  //     },
  //     imageSetPropertiesList: [
  //         {
  //             ImageSetWorkflowStatus: 'CREATED',
  //             createdAt: 2023-09-22T14:49:26.427Z,
  //             imageSetId: 'xxxxxxxxxxxxxxxxxxxxxxx',
  //             imageSetState: 'ACTIVE',
  //             versionId: '1'
  //         }]
  // }
  return imageSetPropertiesList;
};

import { ListTagsForResourceCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} resourceArn - The Amazon Resource Name (ARN) for the data store or image set.
 */
export const listTagsForResource = async (
  resourceArn = "arn:aws:medical-imaging:us-east-1:abc:datastore/def/imageset/ghi",
) => {
  const response = await medicalImagingClient.send(
    new ListTagsForResourceCommand({ resourceArn: resourceArn }),
  );
  console.log(response);
  // {
  //     '$metadata': {
  //         httpStatusCode: 200,
  //         requestId: '008fc6d3-abec-4870-a155-20fa3631e645',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  //     },
  //     tags: { Deployment: 'Development' }
  // }

  return response;
};

用于搜索映像集的实用程序函数。

import { paginateSearchImageSets } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreId - The data store's ID.
 * @param { import('@aws-sdk/client-medical-imaging').SearchFilter[] } filters - The search criteria filters.
 * @param { import('@aws-sdk/client-medical-imaging').Sort } sort - The search criteria sort.
 */
export const searchImageSets = async (
  datastoreId = "xxxxxxxx",
  searchCriteria = {},
) => {
  const paginatorConfig = {
    client: medicalImagingClient,
    pageSize: 50,
  };

  const commandParams = {
    datastoreId: datastoreId,
    searchCriteria: searchCriteria,
  };

  const paginator = paginateSearchImageSets(paginatorConfig, commandParams);

  const imageSetsMetadataSummaries = [];
  for await (const page of paginator) {
    // Each page contains a list of `jobSummaries`. The list is truncated if is larger than `pageSize`.
    imageSetsMetadataSummaries.push(...page.imageSetsMetadataSummaries);
    console.log(page);
  }
  // {
  //     '$metadata': {
  //         httpStatusCode: 200,
  //         requestId: 'f009ea9c-84ca-4749-b5b6-7164f00a5ada',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  //     },
  //     imageSetsMetadataSummaries: [
  //         {
  //             DICOMTags: [Object],
  //             createdAt: "2023-09-19T16:59:40.551Z",
  //             imageSetId: '7f75e1b5c0f40eac2b24cf712f485f50',
  //             updatedAt: "2023-09-19T16:59:40.551Z",
  //             version: 1
  //         }]
  // }

  return imageSetsMetadataSummaries;
};

使用案例 #1：EQUAL 运算符。

  const datastoreId = "12345678901234567890123456789012";

  try {
    const searchCriteria = {
      filters: [
        {
          values: [{ DICOMPatientId: "1234567" }],
          operator: "EQUAL",
        },
      ],
    };

    await searchImageSets(datastoreId, searchCriteria);
  } catch (err) {
    console.error(err);
  }

用例 #2: 使用 DICOMStudy日期和 DICOMStudy时间的 BETWEEN 运算符。

  const datastoreId = "12345678901234567890123456789012";

  try {
    const searchCriteria = {
      filters: [
        {
          values: [
            {
              DICOMStudyDateAndTime: {
                DICOMStudyDate: "19900101",
                DICOMStudyTime: "000000",
              },
            },
            {
              DICOMStudyDateAndTime: {
                DICOMStudyDate: "20230901",
                DICOMStudyTime: "000000",
              },
            },
          ],
          operator: "BETWEEN",
        },
      ],
    };

    await searchImageSets(datastoreId, searchCriteria);
  } catch (err) {
    console.error(err);
  }

使用案例 #3：使用 createdAt 的 BETWEEN 运算符。时间研究以前一直存在。

  const datastoreId = "12345678901234567890123456789012";

  try {
    const searchCriteria = {
      filters: [
        {
          values: [
            { createdAt: new Date("1985-04-12T23:20:50.52Z") },
            { createdAt: new Date() },
          ],
          operator: "BETWEEN",
        },
      ],
    };

    await searchImageSets(datastoreId, searchCriteria);
  } catch (err) {
    console.error(err);
  }

用例 #4: DICOMSeries InstanceUID 上的 EQUAL 运算符和 updateDat 上的 BETWEEN 运算符，在 updateDat 字段上按照 ASC 顺序对响应进行排序。

  const datastoreId = "12345678901234567890123456789012";

  try {
    const searchCriteria = {
      filters: [
        {
          values: [
            { updatedAt: new Date("1985-04-12T23:20:50.52Z") },
            { updatedAt: new Date() },
          ],
          operator: "BETWEEN",
        },
        {
          values: [
            {
              DICOMSeriesInstanceUID:
                "1.1.123.123456.1.12.1.1234567890.1234.12345678.123",
            },
          ],
          operator: "EQUAL",
        },
      ],
      sort: {
        sortOrder: "ASC",
        sortField: "updatedAt",
      },
    };

    await searchImageSets(datastoreId, searchCriteria);
  } catch (err) {
    console.error(err);
  }

import { StartDICOMImportJobCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} jobName - The name of the import job.
 * @param {string} datastoreId - The ID of the data store.
 * @param {string} dataAccessRoleArn - The Amazon Resource Name (ARN) of the role that grants permission.
 * @param {string} inputS3Uri - The URI of the S3 bucket containing the input files.
 * @param {string} outputS3Uri - The URI of the S3 bucket where the output files are stored.
 */
export const startDicomImportJob = async (
  jobName = "test-1",
  datastoreId = "12345678901234567890123456789012",
  dataAccessRoleArn = "arn:aws:iam::xxxxxxxxxxxx:role/ImportJobDataAccessRole",
  inputS3Uri = "s3://medical-imaging-dicom-input/dicom_input/",
  outputS3Uri = "s3://medical-imaging-output/job_output/",
) => {
  const response = await medicalImagingClient.send(
    new StartDICOMImportJobCommand({
      jobName: jobName,
      datastoreId: datastoreId,
      dataAccessRoleArn: dataAccessRoleArn,
      inputS3Uri: inputS3Uri,
      outputS3Uri: outputS3Uri,
    }),
  );
  console.log(response);
  // {
  //     '$metadata': {
  //     httpStatusCode: 200,
  //         requestId: '6e81d191-d46b-4e48-a08a-cdcc7e11eb79',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  // },
  //     datastoreId: 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
  //     jobId: 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
  //     jobStatus: 'SUBMITTED',
  //     submittedAt: 2023-09-22T14:48:45.767Z
  // }
  return response;
};

import { TagResourceCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} resourceArn - The Amazon Resource Name (ARN) for the data store or image set.
 * @param {Record<string,string>} tags - The tags to add to the resource as JSON.
 *                     - For example: {"Deployment" : "Development"}
 */
export const tagResource = async (
  resourceArn = "arn:aws:medical-imaging:us-east-1:xxxxxx:datastore/xxxxx/imageset/xxx",
  tags = {},
) => {
  const response = await medicalImagingClient.send(
    new TagResourceCommand({ resourceArn: resourceArn, tags: tags }),
  );
  console.log(response);
  // {
  //     '$metadata': {
  //        httpStatusCode: 204,
  //         requestId: '8a6de9a3-ec8e-47ef-8643-473518b19d45',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  //    }
  // }

  return response;
};

import { UntagResourceCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} resourceArn - The Amazon Resource Name (ARN) for the data store or image set.
 * @param {string[]} tagKeys - The keys of the tags to remove.
 */
export const untagResource = async (
  resourceArn = "arn:aws:medical-imaging:us-east-1:xxxxxx:datastore/xxxxx/imageset/xxx",
  tagKeys = [],
) => {
  const response = await medicalImagingClient.send(
    new UntagResourceCommand({ resourceArn: resourceArn, tagKeys: tagKeys }),
  );
  console.log(response);
  // {
  //     '$metadata': {
  //        httpStatusCode: 204,
  //         requestId: '8a6de9a3-ec8e-47ef-8643-473518b19d45',
  //         extendedRequestId: undefined,
  //         cfId: undefined,
  //         attempts: 1,
  //         totalRetryDelay: 0
  //    }
  // }

  return response;
};

import { UpdateImageSetMetadataCommand } from "@aws-sdk/client-medical-imaging";
import { medicalImagingClient } from "../libs/medicalImagingClient.js";

/**
 * @param {string} datastoreId - The ID of the HealthImaging data store.
 * @param {string} imageSetId - The ID of the HealthImaging image set.
 * @param {string} latestVersionId - The ID of the HealthImaging image set version.
 * @param {{}} updateMetadata - The metadata to update.
 * @param {boolean} force - Force the update.
 */
export const updateImageSetMetadata = async (
  datastoreId = "xxxxxxxxxx",
  imageSetId = "xxxxxxxxxx",
  latestVersionId = "1",
  updateMetadata = "{}",
  force = false,
) => {
  try {
    const response = await medicalImagingClient.send(
      new UpdateImageSetMetadataCommand({
        datastoreId: datastoreId,
        imageSetId: imageSetId,
        latestVersionId: latestVersionId,
        updateImageSetMetadataUpdates: updateMetadata,
        force: force,
      }),
    );
    console.log(response);
    // {
    //     '$metadata': {
    //     httpStatusCode: 200,
    //         requestId: '7966e869-e311-4bff-92ec-56a61d3003ea',
    //         extendedRequestId: undefined,
    //         cfId: undefined,
    //         attempts: 1,
    //         totalRetryDelay: 0
    // },
    //     createdAt: 2023-09-22T14:49:26.427Z,
    //     datastoreId: 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
    //     imageSetId: 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
    //     imageSetState: 'LOCKED',
    //     imageSetWorkflowStatus: 'UPDATING',
    //     latestVersionId: '4',
    //     updatedAt: 2023-09-27T19:41:43.494Z
    // }
    return response;
  } catch (err) {
    console.error(err);
  }
};

用例 #1: 插入或更新属性并强制更新。

    const insertAttributes = JSON.stringify({
      SchemaVersion: 1.1,
      Study: {
        DICOM: {
          StudyDescription: "CT CHEST",
        },
      },
    });

    const updateMetadata = {
      DICOMUpdates: {
        updatableAttributes: new TextEncoder().encode(insertAttributes),
      },
    };

    await updateImageSetMetadata(
      datastoreID,
      imageSetID,
      versionID,
      updateMetadata,
      true,
    );

用例 #2: 移除属性。

    // Attribute key and value must match the existing attribute.
    const remove_attribute = JSON.stringify({
      SchemaVersion: 1.1,
      Study: {
        DICOM: {
          StudyDescription: "CT CHEST",
        },
      },
    });

    const updateMetadata = {
      DICOMUpdates: {
        removableAttributes: new TextEncoder().encode(remove_attribute),
      },
    };

    await updateImageSetMetadata(
      datastoreID,
      imageSetID,
      versionID,
      updateMetadata,
    );

用例 #3: 移除实例。

    const remove_instance = JSON.stringify({
      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": {},
            },
          },
        },
      },
    });

    const updateMetadata = {
      DICOMUpdates: {
        removableAttributes: new TextEncoder().encode(remove_instance),
      },
    };

    await updateImageSetMetadata(
      datastoreID,
      imageSetID,
      versionID,
      updateMetadata,
    );

用例 #4: 恢复到早期版本。

    const updateMetadata = {
      revertToVersionId: "1",
    };

    await updateImageSetMetadata(
      datastoreID,
      imageSetID,
      versionID,
      updateMetadata,
    );

编排步骤 (index.js).

import {
  parseScenarioArgs,
  Scenario,
} from "@aws-doc-sdk-examples/lib/scenario/index.js";
import {
  saveState,
  loadState,
} from "@aws-doc-sdk-examples/lib/scenario/steps-common.js";

import {
  createStack,
  deployStack,
  getAccountId,
  getDatastoreName,
  getStackName,
  outputState,
  waitForStackCreation,
} from "./deploy-steps.js";
import {
  doCopy,
  selectDataset,
  copyDataset,
  outputCopiedObjects,
} from "./dataset-steps.js";
import {
  doImport,
  outputImportJobStatus,
  startDICOMImport,
  waitForImportJobCompletion,
} from "./import-steps.js";
import {
  getManifestFile,
  outputImageSetIds,
  parseManifestFile,
} from "./image-set-steps.js";
import {
  getImageSetMetadata,
  outputImageFrameIds,
} from "./image-frame-steps.js";
import { decodeAndVerifyImages, doVerify } from "./verify-steps.js";
import {
  confirmCleanup,
  deleteImageSets,
  deleteStack,
} from "./clean-up-steps.js";

const context = {};

const scenarios = {
  deploy: new Scenario(
    "Deploy Resources",
    [
      deployStack,
      getStackName,
      getDatastoreName,
      getAccountId,
      createStack,
      waitForStackCreation,
      outputState,
      saveState,
    ],
    context,
  ),
  demo: new Scenario(
    "Run Demo",
    [
      loadState,
      doCopy,
      selectDataset,
      copyDataset,
      outputCopiedObjects,
      doImport,
      startDICOMImport,
      waitForImportJobCompletion,
      outputImportJobStatus,
      getManifestFile,
      parseManifestFile,
      outputImageSetIds,
      getImageSetMetadata,
      outputImageFrameIds,
      doVerify,
      decodeAndVerifyImages,
      saveState,
    ],
    context,
  ),
  destroy: new Scenario(
    "Clean Up Resources",
    [loadState, confirmCleanup, deleteImageSets, deleteStack],
    context,
  ),
};

// Call function if run directly
import { fileURLToPath } from "node:url";
if (process.argv[1] === fileURLToPath(import.meta.url)) {
  parseScenarioArgs(scenarios, {
    name: "Health Imaging Workflow",
    description:
      "Work with DICOM images using an AWS Health Imaging data store.",
    synopsis:
      "node index.js --scenario <deploy | demo | destroy> [-h|--help] [-y|--yes] [-v|--verbose]",
  });
}

部署资源 (deploy-steps.js).

import fs from "node:fs/promises";
import path from "node:path";

import {
  CloudFormationClient,
  CreateStackCommand,
  DescribeStacksCommand,
} from "@aws-sdk/client-cloudformation";
import { STSClient, GetCallerIdentityCommand } from "@aws-sdk/client-sts";

import {
  ScenarioAction,
  ScenarioInput,
  ScenarioOutput,
} from "@aws-doc-sdk-examples/lib/scenario/index.js";
import { retry } from "@aws-doc-sdk-examples/lib/utils/util-timers.js";

const cfnClient = new CloudFormationClient({});
const stsClient = new STSClient({});

const __dirname = path.dirname(new URL(import.meta.url).pathname);
const cfnTemplatePath = path.join(
  __dirname,
  "../../../../../scenarios/features/healthimaging_image_sets/resources/cfn_template.yaml",
);

export const deployStack = new ScenarioInput(
  "deployStack",
  "Do you want to deploy the CloudFormation stack?",
  { type: "confirm" },
);

export const getStackName = new ScenarioInput(
  "getStackName",
  "Enter a name for the CloudFormation stack:",
  { type: "input", skipWhen: (/** @type {{}} */ state) => !state.deployStack },
);

export const getDatastoreName = new ScenarioInput(
  "getDatastoreName",
  "Enter a name for the HealthImaging datastore:",
  { type: "input", skipWhen: (/** @type {{}} */ state) => !state.deployStack },
);

export const getAccountId = new ScenarioAction(
  "getAccountId",
  async (/** @type {{}} */ state) => {
    const command = new GetCallerIdentityCommand({});
    const response = await stsClient.send(command);
    state.accountId = response.Account;
  },
  {
    skipWhen: (/** @type {{}} */ state) => !state.deployStack,
  },
);

export const createStack = new ScenarioAction(
  "createStack",
  async (/** @type {{}} */ state) => {
    const stackName = state.getStackName;
    const datastoreName = state.getDatastoreName;
    const accountId = state.accountId;

    const command = new CreateStackCommand({
      StackName: stackName,
      TemplateBody: await fs.readFile(cfnTemplatePath, "utf8"),
      Capabilities: ["CAPABILITY_IAM"],
      Parameters: [
        {
          ParameterKey: "datastoreName",
          ParameterValue: datastoreName,
        },
        {
          ParameterKey: "userAccountID",
          ParameterValue: accountId,
        },
      ],
    });

    const response = await cfnClient.send(command);
    state.stackId = response.StackId;
  },
  { skipWhen: (/** @type {{}} */ state) => !state.deployStack },
);

export const waitForStackCreation = new ScenarioAction(
  "waitForStackCreation",
  async (/** @type {{}} */ state) => {
    const command = new DescribeStacksCommand({
      StackName: state.stackId,
    });

    await retry({ intervalInMs: 10000, maxRetries: 60 }, async () => {
      const response = await cfnClient.send(command);
      const stack = response.Stacks?.find(
        (s) => s.StackName === state.getStackName,
      );
      if (!stack || stack.StackStatus === "CREATE_IN_PROGRESS") {
        throw new Error("Stack creation is still in progress");
      }
      if (stack.StackStatus === "CREATE_COMPLETE") {
        state.stackOutputs = stack.Outputs?.reduce((acc, output) => {
          acc[output.OutputKey] = output.OutputValue;
          return acc;
        }, {});
      } else {
        throw new Error(
          `Stack creation failed with status: ${stack.StackStatus}`,
        );
      }
    });
  },
  {
    skipWhen: (/** @type {{}} */ state) => !state.deployStack,
  },
);

export const outputState = new ScenarioOutput(
  "outputState",
  (/** @type {{}} */ state) => {
    /**
     * @type {{ stackOutputs: { DatastoreID: string, BucketName: string, RoleArn: string }}}
     */
    const { stackOutputs } = state;
    return `Stack creation completed. Output values:
Datastore ID: ${stackOutputs?.DatastoreID}
Bucket Name: ${stackOutputs?.BucketName}
Role ARN: ${stackOutputs?.RoleArn}
    `;
  },
  { skipWhen: (/** @type {{}} */ state) => !state.deployStack },
);

复制 DICOM 文件 (dataset-steps.js).

import {
  S3Client,
  CopyObjectCommand,
  ListObjectsV2Command,
} from "@aws-sdk/client-s3";

import {
  ScenarioAction,
  ScenarioInput,
  ScenarioOutput,
} from "@aws-doc-sdk-examples/lib/scenario/index.js";

const s3Client = new S3Client({});

const datasetOptions = [
  {
    name: "CT of chest (2 images)",
    value: "00029d25-fb18-4d42-aaa5-a0897d1ac8f7",
  },
  {
    name: "CT of pelvis (57 images)",
    value: "00025d30-ef8f-4135-a35a-d83eff264fc1",
  },
  {
    name: "MRI of head (192 images)",
    value: "0002d261-8a5d-4e63-8e2e-0cbfac87b904",
  },
  {
    name: "MRI of breast (92 images)",
    value: "0002dd07-0b7f-4a68-a655-44461ca34096",
  },
];

/**
 * @typedef {{ stackOutputs: {
 *   BucketName: string,
 *   DatastoreID: string,
 *   doCopy: boolean
 * }}} State
 */

export const selectDataset = new ScenarioInput(
  "selectDataset",
  (state) => {
    if (!state.doCopy) {
      process.exit(0);
    }
    return "Select a DICOM dataset to import:";
  },
  {
    type: "select",
    choices: datasetOptions,
  },
);

export const doCopy = new ScenarioInput(
  "doCopy",
  "Do you want to copy images from the public dataset into your bucket?",
  {
    type: "confirm",
  },
);

export const copyDataset = new ScenarioAction(
  "copyDataset",
  async (/** @type { State } */ state) => {
    const inputBucket = state.stackOutputs.BucketName;
    const inputPrefix = "input/";
    const selectedDatasetId = state.selectDataset;

    const sourceBucket = "idc-open-data";
    const sourcePrefix = `${selectedDatasetId}`;

    const listObjectsCommand = new ListObjectsV2Command({
      Bucket: sourceBucket,
      Prefix: sourcePrefix,
    });

    const objects = await s3Client.send(listObjectsCommand);

    const copyPromises = objects.Contents.map((object) => {
      const sourceKey = object.Key;
      const destinationKey = `${inputPrefix}${sourceKey
        .split("/")
        .slice(1)
        .join("/")}`;

      const copyCommand = new CopyObjectCommand({
        Bucket: inputBucket,
        CopySource: `/${sourceBucket}/${sourceKey}`,
        Key: destinationKey,
      });

      return s3Client.send(copyCommand);
    });

    const results = await Promise.all(copyPromises);
    state.copiedObjects = results.length;
  },
);

export const outputCopiedObjects = new ScenarioOutput(
  "outputCopiedObjects",
  (state) => `${state.copiedObjects} DICOM files were copied.`,
);

开始导入数据存储 (import-steps.js).

import {
  MedicalImagingClient,
  StartDICOMImportJobCommand,
  GetDICOMImportJobCommand,
} from "@aws-sdk/client-medical-imaging";

import {
  ScenarioAction,
  ScenarioOutput,
  ScenarioInput,
} from "@aws-doc-sdk-examples/lib/scenario/index.js";
import { retry } from "@aws-doc-sdk-examples/lib/utils/util-timers.js";

/**
 * @typedef {{ stackOutputs: {
 *   BucketName: string,
 *   DatastoreID: string,
 *   RoleArn: string
 * }}} State
 */

export const doImport = new ScenarioInput(
  "doImport",
  "Do you want to import DICOM images into your datastore?",
  {
    type: "confirm",
    default: true,
  },
);

export const startDICOMImport = new ScenarioAction(
  "startDICOMImport",
  async (/** @type {State} */ state) => {
    if (!state.doImport) {
      process.exit(0);
    }
    const medicalImagingClient = new MedicalImagingClient({});
    const inputS3Uri = `s3://${state.stackOutputs.BucketName}/input/`;
    const outputS3Uri = `s3://${state.stackOutputs.BucketName}/output/`;

    const command = new StartDICOMImportJobCommand({
      dataAccessRoleArn: state.stackOutputs.RoleArn,
      datastoreId: state.stackOutputs.DatastoreID,
      inputS3Uri,
      outputS3Uri,
    });

    const response = await medicalImagingClient.send(command);
    state.importJobId = response.jobId;
  },
);

export const waitForImportJobCompletion = new ScenarioAction(
  "waitForImportJobCompletion",
  async (/** @type {State} */ state) => {
    const medicalImagingClient = new MedicalImagingClient({});
    const command = new GetDICOMImportJobCommand({
      datastoreId: state.stackOutputs.DatastoreID,
      jobId: state.importJobId,
    });

    await retry({ intervalInMs: 10000, maxRetries: 60 }, async () => {
      const response = await medicalImagingClient.send(command);
      const jobStatus = response.jobProperties?.jobStatus;
      if (!jobStatus || jobStatus === "IN_PROGRESS") {
        throw new Error("Import job is still in progress");
      }
      if (jobStatus === "COMPLETED") {
        state.importJobOutputS3Uri = response.jobProperties.outputS3Uri;
      } else {
        throw new Error(`Import job failed with status: ${jobStatus}`);
      }
    });
  },
);

export const outputImportJobStatus = new ScenarioOutput(
  "outputImportJobStatus",
  (state) =>
    `DICOM import job completed. Output location: ${state.importJobOutputS3Uri}`,
);

获取图像集 IDs (image-set-steps.js - ).

import { S3Client, GetObjectCommand } from "@aws-sdk/client-s3";

import {
  ScenarioAction,
  ScenarioOutput,
} from "@aws-doc-sdk-examples/lib/scenario/index.js";

/**
 * @typedef {{ stackOutputs: {
 *   BucketName: string,
 *   DatastoreID: string,
 *   RoleArn: string
 * }, importJobId: string,
 * importJobOutputS3Uri: string,
 * imageSetIds: string[],
 * manifestContent: { jobSummary: { imageSetsSummary: { imageSetId: string }[] } }
 * }} State
 */

const s3Client = new S3Client({});

export const getManifestFile = new ScenarioAction(
  "getManifestFile",
  async (/** @type {State} */ state) => {
    const bucket = state.stackOutputs.BucketName;
    const prefix = `output/${state.stackOutputs.DatastoreID}-DicomImport-${state.importJobId}/`;
    const key = `${prefix}job-output-manifest.json`;

    const command = new GetObjectCommand({
      Bucket: bucket,
      Key: key,
    });

    const response = await s3Client.send(command);
    const manifestContent = await response.Body.transformToString();
    state.manifestContent = JSON.parse(manifestContent);
  },
);

export const parseManifestFile = new ScenarioAction(
  "parseManifestFile",
  (/** @type {State} */ state) => {
    const imageSetIds =
      state.manifestContent.jobSummary.imageSetsSummary.reduce((ids, next) => {
        return Object.assign({}, ids, {
          [next.imageSetId]: next.imageSetId,
        });
      }, {});
    state.imageSetIds = Object.keys(imageSetIds);
  },
);

export const outputImageSetIds = new ScenarioOutput(
  "outputImageSetIds",
  (/** @type {State} */ state) =>
    `The image sets created by this import job are: \n${state.imageSetIds
      .map((id) => `Image set: ${id}`)
      .join("\n")}`,
);

获取图像框架 IDs (image-frame-steps.js).

import {
  MedicalImagingClient,
  GetImageSetMetadataCommand,
} from "@aws-sdk/client-medical-imaging";
import { gunzip } from "node:zlib";
import { promisify } from "node:util";

import {
  ScenarioAction,
  ScenarioOutput,
} from "@aws-doc-sdk-examples/lib/scenario/index.js";

const gunzipAsync = promisify(gunzip);

/**
 * @typedef {Object} DICOMValueRepresentation
 * @property {string} name
 * @property {string} type
 * @property {string} value
 */

/**
 * @typedef {Object} ImageFrameInformation
 * @property {string} ID
 * @property {Array<{ Checksum: number, Height: number, Width: number }>} PixelDataChecksumFromBaseToFullResolution
 * @property {number} MinPixelValue
 * @property {number} MaxPixelValue
 * @property {number} FrameSizeInBytes
 */

/**
 * @typedef {Object} DICOMMetadata
 * @property {Object} DICOM
 * @property {DICOMValueRepresentation[]} DICOMVRs
 * @property {ImageFrameInformation[]} ImageFrames
 */

/**
 * @typedef {Object} Series
 * @property {{ [key: string]: DICOMMetadata }} Instances
 */

/**
 * @typedef {Object} Study
 * @property {Object} DICOM
 * @property {Series[]} Series
 */

/**
 * @typedef {Object} Patient
 * @property {Object} DICOM
 */

/**
 * @typedef {{
 *  SchemaVersion: string,
 *  DatastoreID: string,
 *  ImageSetID: string,
 *  Patient: Patient,
 *  Study: Study
 * }} ImageSetMetadata
 */

/**
 * @typedef {{ stackOutputs: {
 *   BucketName: string,
 *   DatastoreID: string,
 *   RoleArn: string
 * }, imageSetIds: string[] }} State
 */

const medicalImagingClient = new MedicalImagingClient({});

export const getImageSetMetadata = new ScenarioAction(
  "getImageSetMetadata",
  async (/** @type {State} */ state) => {
    const outputMetadata = [];

    for (const imageSetId of state.imageSetIds) {
      const command = new GetImageSetMetadataCommand({
        datastoreId: state.stackOutputs.DatastoreID,
        imageSetId,
      });

      const response = await medicalImagingClient.send(command);
      const compressedMetadataBlob =
        await response.imageSetMetadataBlob.transformToByteArray();
      const decompressedMetadata = await gunzipAsync(compressedMetadataBlob);
      const imageSetMetadata = JSON.parse(decompressedMetadata.toString());

      outputMetadata.push(imageSetMetadata);
    }

    state.imageSetMetadata = outputMetadata;
  },
);

export const outputImageFrameIds = new ScenarioOutput(
  "outputImageFrameIds",
  (/** @type {State & { imageSetMetadata: ImageSetMetadata[] }} */ state) => {
    let output = "";

    for (const metadata of state.imageSetMetadata) {
      const imageSetId = metadata.ImageSetID;
      /** @type {DICOMMetadata[]} */
      const instances = Object.values(metadata.Study.Series).flatMap(
        (series) => {
          return Object.values(series.Instances);
        },
      );
      const imageFrameIds = instances.flatMap((instance) =>
        instance.ImageFrames.map((frame) => frame.ID),
      );

      output += `Image set ID: ${imageSetId}\nImage frame IDs:\n${imageFrameIds.join(
        "\n",
      )}\n\n`;
    }

    return output;
  },
);

验证图像帧 (verify-steps.js)。 使用AWS HealthImaging 像素数据验证库进行验证。

import { spawn } from "node:child_process";

import {
  ScenarioAction,
  ScenarioInput,
} from "@aws-doc-sdk-examples/lib/scenario/index.js";

/**
 * @typedef {Object} DICOMValueRepresentation
 * @property {string} name
 * @property {string} type
 * @property {string} value
 */

/**
 * @typedef {Object} ImageFrameInformation
 * @property {string} ID
 * @property {Array<{ Checksum: number, Height: number, Width: number }>} PixelDataChecksumFromBaseToFullResolution
 * @property {number} MinPixelValue
 * @property {number} MaxPixelValue
 * @property {number} FrameSizeInBytes
 */

/**
 * @typedef {Object} DICOMMetadata
 * @property {Object} DICOM
 * @property {DICOMValueRepresentation[]} DICOMVRs
 * @property {ImageFrameInformation[]} ImageFrames
 */

/**
 * @typedef {Object} Series
 * @property {{ [key: string]: DICOMMetadata }} Instances
 */

/**
 * @typedef {Object} Study
 * @property {Object} DICOM
 * @property {Series[]} Series
 */

/**
 * @typedef {Object} Patient
 * @property {Object} DICOM
 */

/**
 * @typedef {{
 *  SchemaVersion: string,
 *  DatastoreID: string,
 *  ImageSetID: string,
 *  Patient: Patient,
 *  Study: Study
 * }} ImageSetMetadata
 */

/**
 * @typedef {{ stackOutputs: {
 *   BucketName: string,
 *   DatastoreID: string,
 *   RoleArn: string
 * }, imageSetMetadata: ImageSetMetadata[] }} State
 */

export const doVerify = new ScenarioInput(
  "doVerify",
  "Do you want to verify the imported images?",
  {
    type: "confirm",
    default: true,
  },
);

export const decodeAndVerifyImages = new ScenarioAction(
  "decodeAndVerifyImages",
  async (/** @type {State} */ state) => {
    if (!state.doVerify) {
      process.exit(0);
    }
    const verificationTool = "./pixel-data-verification/index.js";

    for (const metadata of state.imageSetMetadata) {
      const datastoreId = state.stackOutputs.DatastoreID;
      const imageSetId = metadata.ImageSetID;

      for (const [seriesInstanceUid, series] of Object.entries(
        metadata.Study.Series,
      )) {
        for (const [sopInstanceUid, _] of Object.entries(series.Instances)) {
          console.log(
            `Verifying image set ${imageSetId} with series ${seriesInstanceUid} and sop ${sopInstanceUid}`,
          );
          const child = spawn(
            "node",
            [
              verificationTool,
              datastoreId,
              imageSetId,
              seriesInstanceUid,
              sopInstanceUid,
            ],
            { stdio: "inherit" },
          );

          await new Promise((resolve, reject) => {
            child.on("exit", (code) => {
              if (code === 0) {
                resolve();
              } else {
                reject(
                  new Error(
                    `Verification tool exited with code ${code} for image set ${imageSetId}`,
                  ),
                );
              }
            });
          });
        }
      }
    }
  },
);

销毁资源 (clean-up-steps.js).

import {
  CloudFormationClient,
  DeleteStackCommand,
} from "@aws-sdk/client-cloudformation";
import {
  MedicalImagingClient,
  DeleteImageSetCommand,
} from "@aws-sdk/client-medical-imaging";

import {
  ScenarioAction,
  ScenarioInput,
} from "@aws-doc-sdk-examples/lib/scenario/index.js";

/**
 * @typedef {Object} DICOMValueRepresentation
 * @property {string} name
 * @property {string} type
 * @property {string} value
 */

/**
 * @typedef {Object} ImageFrameInformation
 * @property {string} ID
 * @property {Array<{ Checksum: number, Height: number, Width: number }>} PixelDataChecksumFromBaseToFullResolution
 * @property {number} MinPixelValue
 * @property {number} MaxPixelValue
 * @property {number} FrameSizeInBytes
 */

/**
 * @typedef {Object} DICOMMetadata
 * @property {Object} DICOM
 * @property {DICOMValueRepresentation[]} DICOMVRs
 * @property {ImageFrameInformation[]} ImageFrames
 */

/**
 * @typedef {Object} Series
 * @property {{ [key: string]: DICOMMetadata }} Instances
 */

/**
 * @typedef {Object} Study
 * @property {Object} DICOM
 * @property {Series[]} Series
 */

/**
 * @typedef {Object} Patient
 * @property {Object} DICOM
 */

/**
 * @typedef {{
 *  SchemaVersion: string,
 *  DatastoreID: string,
 *  ImageSetID: string,
 *  Patient: Patient,
 *  Study: Study
 * }} ImageSetMetadata
 */

/**
 * @typedef {{ stackOutputs: {
 *   BucketName: string,
 *   DatastoreID: string,
 *   RoleArn: string
 * }, imageSetMetadata: ImageSetMetadata[] }} State
 */

const cfnClient = new CloudFormationClient({});
const medicalImagingClient = new MedicalImagingClient({});

export const confirmCleanup = new ScenarioInput(
  "confirmCleanup",
  "Do you want to delete the created resources?",
  { type: "confirm" },
);

export const deleteImageSets = new ScenarioAction(
  "deleteImageSets",
  async (/** @type {State} */ state) => {
    const datastoreId = state.stackOutputs.DatastoreID;

    for (const metadata of state.imageSetMetadata) {
      const command = new DeleteImageSetCommand({
        datastoreId,
        imageSetId: metadata.ImageSetID,
      });

      try {
        await medicalImagingClient.send(command);
        console.log(`Successfully deleted image set ${metadata.ImageSetID}`);
      } catch (e) {
        if (e instanceof Error) {
          if (e.name === "ConflictException") {
            console.log(`Image set ${metadata.ImageSetID} already deleted`);
          }
        }
      }
    }
  },
  {
    skipWhen: (/** @type {{}} */ state) => !state.confirmCleanup,
  },
);

export const deleteStack = new ScenarioAction(
  "deleteStack",
  async (/** @type {State} */ state) => {
    const stackName = state.getStackName;

    const command = new DeleteStackCommand({
      StackName: stackName,
    });

    await cfnClient.send(command);
    console.log(`Stack ${stackName} deletion initiated`);
  },
  {
    skipWhen: (/** @type {{}} */ state) => !state.confirmCleanup,
  },
);