HealthImaging 使用适用于 JavaScript (v3) 的 SDK 的示例 - Amazon SDK for JavaScript
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Amazon SDK for JavaScript V3 API 参考指南详细描述了 Amazon SDK for JavaScript 版本 3 (V3) 的所有 API 操作。

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

以下代码示例向您展示了如何通过使用 Amazon SDK for JavaScript (v3) 来执行操作和实现常见场景 HealthImaging。

操作是大型程序的代码摘录,必须在上下文中运行。您可以通过操作了解如何调用单个服务函数,还可以通过函数相关场景和跨服务示例的上下文查看操作。

场景 是展示如何通过在同一服务中调用多个函数来完成特定任务的代码示例。

每个示例都包含一个指向的链接 GitHub,您可以在其中找到有关如何在上下文中设置和运行代码的说明。

开始使用

以下代码示例显示了如何开始使用 HealthImaging。

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考ListDatastores中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

操作

以下代码示例演示了如何使用 CopyImageSet

适用于 JavaScript (v3) 的软件开发工具包

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. */ export const copyImageSet = async ( datastoreId = "xxxxxxxxxxx", imageSetId = "xxxxxxxxxxxx", sourceVersionId = "1", destinationImageSetId = "", destinationVersionId = "" ) => { const params = { datastoreId: datastoreId, sourceImageSetId: imageSetId, copyImageSetInformation: { sourceImageSet: { latestVersionId: sourceVersionId }, }, }; if (destinationImageSetId !== "" && destinationVersionId !== "") { params.copyImageSetInformation.destinationImageSet = { imageSetId: destinationImageSetId, latestVersionId: destinationVersionId, }; } 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; };

复制没有目标的映像集。

try { await copyImageSet( "12345678901234567890123456789012", "12345678901234567890123456789012", "1" ); } catch (err) { console.error(err); }

复制带有目标的映像集。

try { await copyImageSet( "12345678901234567890123456789012", "12345678901234567890123456789012", "4", "12345678901234567890123456789012", "1" ); } catch (err) { console.error(err); }
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考中的CopyImage设置

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 CreateDatastore

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考CreateDatastore中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 DeleteDatastore

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考DeleteDatastore中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 DeleteImageSet

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考中的DeleteImage设置

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 GetDICOMImportJob

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript AP I 参考ImportJob中的 getDicom

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 GetDatastore

适用于 JavaScript (v3) 的软件开发工具包
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"]; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考GetDatastore中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 GetImageFrame

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考中的GetImage框架

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 GetImageSet

适用于 JavaScript (v3) 的软件开发工具包
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 = "" ) => { let 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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考中的GetImage设置

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 GetImageSetMetadata

适用于 JavaScript (v3) 的软件开发工具包

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 "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); }
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考GetImageSetMetadata中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 ListDICOMImportJobs

适用于 JavaScript (v3) 的软件开发工具包
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); let 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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript AP I 参考ImportJobs中的 ListDicom

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 ListDatastores

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考ListDatastores中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 ListImageSetVersions

适用于 JavaScript (v3) 的软件开发工具包
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 ); let 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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考ListImageSetVersions中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 ListTagsForResource

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考ListTagsForResource中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 SearchImageSets

适用于 JavaScript (v3) 的软件开发工具包

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: 在使用 DICOM 和 DICOM 的运算符之间StudyDate 。StudyTime

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: DICOM SeriesInstance UID 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); }
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考中的SearchImage集合

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 StartDICOMImportJob

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript AP I 参考ImportJob中的 StartDicom

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 TagResource

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考TagResource中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 UntagResource

适用于 JavaScript (v3) 的软件开发工具包
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; };
  • 有关 API 的详细信息,请参阅 Amazon SDK for JavaScript API 参考UntagResource中的。

注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例演示了如何使用 UpdateImageSetMetadata

适用于 JavaScript (v3) 的软件开发工具包
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. */ export const updateImageSetMetadata = async (datastoreId = "xxxxxxxxxx", imageSetId = "xxxxxxxxxx", latestVersionId = "1", updateMetadata = '{}') => { const response = await medicalImagingClient.send( new UpdateImageSetMetadataCommand({ datastoreId: datastoreId, imageSetId: imageSetId, latestVersionId: latestVersionId, updateImageSetMetadataUpdates: updateMetadata }) ); 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; };

用例 #1: 插入或更新属性。

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);

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);
注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

场景

以下代码示例说明如何导入 DICOM 文件和在中下载图像框架。 HealthImaging

该实现结构为工作流命令行应用程序。

  • 设置 DICOM 导入的资源。

  • 将 DICOM 文件导入数据存储中。

  • 检索导入任务的影像集 ID。

  • 检索影像集的影像帧 ID。

  • 下载、解码并验证影像帧。

  • 清理资源。

适用于 JavaScript (v3) 的软件开发工具包

index.js-编排步骤。

// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. // SPDX-License-Identifier: Apache-2.0 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 "url"; if (process.argv[1] === fileURLToPath(import.meta.url)) { parseScenarioArgs(scenarios); }

deploy-steps.js-部署资源。

// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. // SPDX-License-Identifier: Apache-2.0 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, "../../../../../workflows/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 }, );

dataset-steps.js-复制 DICOM 文件。

// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. // SPDX-License-Identifier: Apache-2.0 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.`, );

import-steps.js-开始导入数据存储。

// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. // SPDX-License-Identifier: Apache-2.0 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", }, ); 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}`, );

image-set-steps.js-获取图像集 ID。

// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. // SPDX-License-Identifier: Apache-2.0 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 = `${prefix}job-output-manifest.json`; const command = new GetObjectCommand({ Bucket: bucket, Key: key, }); const response = await s3Client.send(command); const manifestContent = await response.Body.transformToString(); state.manifestContent = JSON.parse(manifestContent); }, ); export const parseManifestFile = new ScenarioAction( "parseManifestFile", (/** @type {State} */ state) => { const imageSetIds = state.manifestContent.jobSummary.imageSetsSummary.reduce( (imageSetIds, next) => { return { ...imageSetIds, [next.imageSetId]: next.imageSetId }; }, {}, ); state.imageSetIds = Object.keys(imageSetIds); }, ); export const outputImageSetIds = new ScenarioOutput( "outputImageSetIds", (/** @type {State} */ state) => `The image sets created by this import job are: \n${state.imageSetIds .map((id) => `Image set: ${id}`) .join("\n")}`, );

image-frame-steps.js-获取图像框 ID。

// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. // SPDX-License-Identifier: Apache-2.0 import { MedicalImagingClient, GetImageSetMetadataCommand, } from "@aws-sdk/client-medical-imaging"; import { gunzip } from "zlib"; import { promisify } from "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; }, { slow: false }, );

verify-steps.js-验证图像框。使用Amazon HealthImaging 像素数据验证库进行验证。

// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. // SPDX-License-Identifier: Apache-2.0 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", }, ); 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}`, ), ); } }); }); } } } }, );

clean-up-steps.js-摧毁资源。

// Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. // SPDX-License-Identifier: Apache-2.0 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, }, );
注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例显示了如何为 HealthImaging 数据存储添加标签。

适用于 JavaScript (v3) 的软件开发工具包

标记数据存储。

try { const datastoreArn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012"; const tags = { Deployment: "Development", }; await tagResource(datastoreArn, tags); } catch (e) { console.log(e); }

用于标记资源的实用程序函数。

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; };

列出数据存储的标签。

try { const datastoreArn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012"; const { tags } = await listTagsForResource(datastoreArn); console.log(tags); } catch (e) { console.log(e); }

用于列出资源标签的实用程序函数。

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; };

取消标记数据存储。

try { const datastoreArn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012"; const keys = ["Deployment"]; await untagResource(datastoreArn, keys); } catch (e) { console.log(e); }

用于取消标记资源的实用程序函数。

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; };
注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。

以下代码示例显示了如何为 HealthImaging 图像集添加标签。

适用于 JavaScript (v3) 的软件开发工具包

标记映像集。

try { const imagesetArn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012/imageset/12345678901234567890123456789012"; const tags = { Deployment: "Development", }; await tagResource(imagesetArn, tags); } catch (e) { console.log(e); }

用于标记资源的实用程序函数。

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; };

列出映像集的标签。

try { const imagesetArn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012/imageset/12345678901234567890123456789012"; const { tags } = await listTagsForResource(imagesetArn); console.log(tags); } catch (e) { console.log(e); }

用于列出资源标签的实用程序函数。

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; };

取消标记映像集。

try { const imagesetArn = "arn:aws:medical-imaging:us-east-1:123456789012:datastore/12345678901234567890123456789012/imageset/12345678901234567890123456789012"; const keys = ["Deployment"]; await untagResource(imagesetArn, keys); } catch (e) { console.log(e); }

用于取消标记资源的实用程序函数。

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; };
注意

还有更多相关信息 GitHub。在 Amazon 代码示例存储库中查找完整示例,了解如何进行设置和运行。