AWS SDK を使用して HealthImaging 画像セットと画像フレームの使用を開始する - AWS SDK コード例

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AWS SDK を使用して HealthImaging 画像セットと画像フレームの使用を開始する

次のコード例は、 で DICOM ファイルをインポートし、イメージフレームをダウンロードする方法を示しています HealthImaging。

実装はワークフローコマンドラインアプリケーションとして構造化されています。

  • DICOM インポートするためのリソースのセットアップ

  • DICOM ファイルをデータストアへのインポート。

  • インポートジョブの画像セット ID の取得。

  • インポートジョブの画像フレーム ID の取得。

  • イメージフレームをダウンロード、デコード、および検証します。

  • リソースをクリーンアップします。

C++
SDK for C++

必要なリソースを含む AWS CloudFormation スタックを作成します。

Aws::String inputBucketName; Aws::String outputBucketName; Aws::String dataStoreId; Aws::String roleArn; Aws::String stackName; if (askYesNoQuestion( "Would you like to let this workflow create the resources for you? (y/n) ")) { stackName = askQuestion( "Enter a name for the AWS CloudFormation stack to create. "); Aws::String dataStoreName = askQuestion( "Enter a name for the HealthImaging datastore to create. "); Aws::Map<Aws::String, Aws::String> outputs = createCloudFormationStack( stackName, dataStoreName, clientConfiguration); if (!retrieveOutputs(outputs, dataStoreId, inputBucketName, outputBucketName, roleArn)) { return false; } std::cout << "The following resources have been created." << std::endl; std::cout << "A HealthImaging datastore with ID: " << dataStoreId << "." << std::endl; std::cout << "An Amazon S3 input bucket named: " << inputBucketName << "." << std::endl; std::cout << "An Amazon S3 output bucket named: " << outputBucketName << "." << std::endl; std::cout << "An IAM role with the ARN: " << roleArn << "." << std::endl; askQuestion("Enter return to continue.", alwaysTrueTest); } else { std::cout << "You have chosen to use preexisting resources:" << std::endl; dataStoreId = askQuestion( "Enter the data store ID of the HealthImaging datastore you wish to use: "); inputBucketName = askQuestion( "Enter the name of the S3 input bucket you wish to use: "); outputBucketName = askQuestion( "Enter the name of the S3 output bucket you wish to use: "); roleArn = askQuestion( "Enter the ARN for the IAM role with the proper permissions to import a DICOM series: "); }

DICOM ファイルを Amazon S3 インポートバケットにコピーします。

std::cout << "This workflow uses DICOM files from the National Cancer Institute Imaging Data\n" << "Commons (IDC) Collections." << std::endl; std::cout << "Here is the link to their website." << std::endl; std::cout << "https://registry.opendata.aws/nci-imaging-data-commons/" << std::endl; std::cout << "We will use DICOM files stored in an S3 bucket managed by the IDC." << std::endl; std::cout << "First one of the DICOM folders in the IDC collection must be copied to your\n" "input S3 bucket." << std::endl; std::cout << "You have the choice of one of the following " << IDC_ImageChoices.size() << " folders to copy." << std::endl; int index = 1; for (auto &idcChoice: IDC_ImageChoices) { std::cout << index << " - " << idcChoice.mDescription << std::endl; index++; } int choice = askQuestionForIntRange("Choose DICOM files to import: ", 1, 4); Aws::String fromDirectory = IDC_ImageChoices[choice - 1].mDirectory; Aws::String inputDirectory = "input"; std::cout << "The files in the directory '" << fromDirectory << "' in the bucket '" << IDC_S3_BucketName << "' will be copied " << std::endl; std::cout << "to the folder '" << inputDirectory << "/" << fromDirectory << "' in the bucket '" << inputBucketName << "'." << std::endl; askQuestion("Enter return to start the copy.", alwaysTrueTest); if (!AwsDoc::Medical_Imaging::copySeriesBetweenBuckets( IDC_S3_BucketName, fromDirectory, inputBucketName, inputDirectory, clientConfiguration)) { std::cerr << "This workflow will exit because of an error." << std::endl; cleanup(stackName, dataStoreId, clientConfiguration); return false; }

DICOM ファイルを Amazon S3 データストアのにインポートします。

bool AwsDoc::Medical_Imaging::startDicomImport(const Aws::String &dataStoreID, const Aws::String &inputBucketName, const Aws::String &inputDirectory, const Aws::String &outputBucketName, const Aws::String &outputDirectory, const Aws::String &roleArn, Aws::String &importJobId, const Aws::Client::ClientConfiguration &clientConfiguration) { bool result = false; if (startDICOMImportJob(dataStoreID, inputBucketName, inputDirectory, outputBucketName, outputDirectory, roleArn, importJobId, clientConfiguration)) { std::cout << "DICOM import job started with job ID " << importJobId << "." << std::endl; result = waitImportJobCompleted(dataStoreID, importJobId, clientConfiguration); if (result) { std::cout << "DICOM import job completed." << std::endl; } } return result; } //! Routine which starts a HealthImaging import job. /*! \param dataStoreID: The HealthImaging data store ID. \param inputBucketName: The name of the Amazon S3 bucket containing the DICOM files. \param inputDirectory: The directory in the S3 bucket containing the DICOM files. \param outputBucketName: The name of the S3 bucket for the output. \param outputDirectory: The directory in the S3 bucket to store the output. \param roleArn: The ARN of the IAM role with permissions for the import. \param importJobId: A string to receive the import job ID. \param clientConfig: Aws client configuration. \return bool: Function succeeded. */ bool AwsDoc::Medical_Imaging::startDICOMImportJob( const Aws::String &dataStoreID, const Aws::String &inputBucketName, const Aws::String &inputDirectory, const Aws::String &outputBucketName, const Aws::String &outputDirectory, const Aws::String &roleArn, Aws::String &importJobId, const Aws::Client::ClientConfiguration &clientConfig) { Aws::MedicalImaging::MedicalImagingClient medicalImagingClient(clientConfig); Aws::String inputURI = "s3://" + inputBucketName + "/" + inputDirectory + "/"; Aws::String outputURI = "s3://" + outputBucketName + "/" + outputDirectory + "/"; Aws::MedicalImaging::Model::StartDICOMImportJobRequest startDICOMImportJobRequest; startDICOMImportJobRequest.SetDatastoreId(dataStoreID); startDICOMImportJobRequest.SetDataAccessRoleArn(roleArn); startDICOMImportJobRequest.SetInputS3Uri(inputURI); startDICOMImportJobRequest.SetOutputS3Uri(outputURI); Aws::MedicalImaging::Model::StartDICOMImportJobOutcome startDICOMImportJobOutcome = medicalImagingClient.StartDICOMImportJob( startDICOMImportJobRequest); if (startDICOMImportJobOutcome.IsSuccess()) { importJobId = startDICOMImportJobOutcome.GetResult().GetJobId(); } else { std::cerr << "Failed to start DICOM import job because " << startDICOMImportJobOutcome.GetError().GetMessage() << std::endl; } return startDICOMImportJobOutcome.IsSuccess(); } //! Routine which waits for a DICOM import job to complete. /*! * @param dataStoreID: The HealthImaging data store ID. * @param importJobId: The import job ID. * @param clientConfiguration : Aws client configuration. * @return bool: Function succeeded. */ bool AwsDoc::Medical_Imaging::waitImportJobCompleted(const Aws::String &datastoreID, const Aws::String &importJobId, const Aws::Client::ClientConfiguration &clientConfiguration) { Aws::MedicalImaging::Model::JobStatus jobStatus = Aws::MedicalImaging::Model::JobStatus::IN_PROGRESS; while (jobStatus == Aws::MedicalImaging::Model::JobStatus::IN_PROGRESS) { std::this_thread::sleep_for(std::chrono::seconds(1)); Aws::MedicalImaging::Model::GetDICOMImportJobOutcome getDicomImportJobOutcome = getDICOMImportJob( datastoreID, importJobId, clientConfiguration); if (getDicomImportJobOutcome.IsSuccess()) { jobStatus = getDicomImportJobOutcome.GetResult().GetJobProperties().GetJobStatus(); std::cout << "DICOM import job status: " << Aws::MedicalImaging::Model::JobStatusMapper::GetNameForJobStatus( jobStatus) << std::endl; } else { std::cerr << "Failed to get import job status because " << getDicomImportJobOutcome.GetError().GetMessage() << std::endl; return false; } } return jobStatus == Aws::MedicalImaging::Model::JobStatus::COMPLETED; } //! Routine which gets a HealthImaging DICOM import job's properties. /*! \param dataStoreID: The HealthImaging data store ID. \param importJobID: The DICOM import job ID \param clientConfig: Aws client configuration. \return GetDICOMImportJobOutcome: The import job outcome. */ Aws::MedicalImaging::Model::GetDICOMImportJobOutcome AwsDoc::Medical_Imaging::getDICOMImportJob(const Aws::String &dataStoreID, const Aws::String &importJobID, const Aws::Client::ClientConfiguration &clientConfig) { Aws::MedicalImaging::MedicalImagingClient client(clientConfig); Aws::MedicalImaging::Model::GetDICOMImportJobRequest request; request.SetDatastoreId(dataStoreID); request.SetJobId(importJobID); Aws::MedicalImaging::Model::GetDICOMImportJobOutcome outcome = client.GetDICOMImportJob( request); if (!outcome.IsSuccess()) { std::cerr << "GetDICOMImportJob error: " << outcome.GetError().GetMessage() << std::endl; } return outcome; }

DICOM インポートジョブによって作成された画像セットを取得します。

bool AwsDoc::Medical_Imaging::getImageSetsForDicomImportJob(const Aws::String &datastoreID, const Aws::String &importJobId, Aws::Vector<Aws::String> &imageSets, const Aws::Client::ClientConfiguration &clientConfiguration) { Aws::MedicalImaging::Model::GetDICOMImportJobOutcome getDicomImportJobOutcome = getDICOMImportJob( datastoreID, importJobId, clientConfiguration); bool result = false; if (getDicomImportJobOutcome.IsSuccess()) { auto outputURI = getDicomImportJobOutcome.GetResult().GetJobProperties().GetOutputS3Uri(); Aws::Http::URI uri(outputURI); const Aws::String &bucket = uri.GetAuthority(); Aws::String key = uri.GetPath(); Aws::S3::S3Client s3Client(clientConfiguration); Aws::S3::Model::GetObjectRequest objectRequest; objectRequest.SetBucket(bucket); objectRequest.SetKey(key + "/" + IMPORT_JOB_MANIFEST_FILE_NAME); auto getObjectOutcome = s3Client.GetObject(objectRequest); if (getObjectOutcome.IsSuccess()) { auto &data = getObjectOutcome.GetResult().GetBody(); std::stringstream stringStream; stringStream << data.rdbuf(); try { // Use JMESPath to extract the image set IDs. // https://jmespath.org/specification.html std::string jmesPathExpression = "jobSummary.imageSetsSummary[].imageSetId"; jsoncons::json doc = jsoncons::json::parse(stringStream.str()); jsoncons::json imageSetsJson = jsoncons::jmespath::search(doc, jmesPathExpression);\ for (auto &imageSet: imageSetsJson.array_range()) { imageSets.push_back(imageSet.as_string()); } result = true; } catch (const std::exception &e) { std::cerr << e.what() << '\n'; } } else { std::cerr << "Failed to get object because " << getObjectOutcome.GetError().GetMessage() << std::endl; } } else { std::cerr << "Failed to get import job status because " << getDicomImportJobOutcome.GetError().GetMessage() << std::endl; } return result; }

画像セットの画像フレーム情報を取得します。

bool AwsDoc::Medical_Imaging::getImageFramesForImageSet(const Aws::String &dataStoreID, const Aws::String &imageSetID, const Aws::String &outDirectory, Aws::Vector<ImageFrameInfo> &imageFrames, const Aws::Client::ClientConfiguration &clientConfiguration) { Aws::String fileName = outDirectory + "/" + imageSetID + "_metadata.json.gzip"; bool result = false; if (getImageSetMetadata(dataStoreID, imageSetID, "", // Empty string for version ID. fileName, clientConfiguration)) { try { std::string metadataGZip; { std::ifstream inFileStream(fileName.c_str(), std::ios::binary); if (!inFileStream) { throw std::runtime_error("Failed to open file " + fileName); } std::stringstream stringStream; stringStream << inFileStream.rdbuf(); metadataGZip = stringStream.str(); } std::string metadataJson = gzip::decompress(metadataGZip.data(), metadataGZip.size()); // Use JMESPath to extract the image set IDs. // https://jmespath.org/specification.html jsoncons::json doc = jsoncons::json::parse(metadataJson); std::string jmesPathExpression = "Study.Series.*.Instances[].*[]"; jsoncons::json instances = jsoncons::jmespath::search(doc, jmesPathExpression); for (auto &instance: instances.array_range()) { jmesPathExpression = "DICOM.RescaleSlope"; std::string rescaleSlope = jsoncons::jmespath::search(instance, jmesPathExpression).to_string(); jmesPathExpression = "DICOM.RescaleIntercept"; std::string rescaleIntercept = jsoncons::jmespath::search(instance, jmesPathExpression).to_string(); jmesPathExpression = "ImageFrames[][]"; jsoncons::json imageFramesJson = jsoncons::jmespath::search(instance, jmesPathExpression); for (auto &imageFrame: imageFramesJson.array_range()) { ImageFrameInfo imageFrameIDs; imageFrameIDs.mImageSetId = imageSetID; imageFrameIDs.mImageFrameId = imageFrame.find( "ID")->value().as_string(); imageFrameIDs.mRescaleIntercept = rescaleIntercept; imageFrameIDs.mRescaleSlope = rescaleSlope; imageFrameIDs.MinPixelValue = imageFrame.find( "MinPixelValue")->value().as_string(); imageFrameIDs.MaxPixelValue = imageFrame.find( "MaxPixelValue")->value().as_string(); jmesPathExpression = "max_by(PixelDataChecksumFromBaseToFullResolution, &Width).Checksum"; jsoncons::json checksumJson = jsoncons::jmespath::search(imageFrame, jmesPathExpression); imageFrameIDs.mFullResolutionChecksum = checksumJson.as_integer<uint32_t>(); imageFrames.emplace_back(imageFrameIDs); } } result = true; } catch (const std::exception &e) { std::cerr << "getImageFramesForImageSet failed because " << e.what() << std::endl; } } return result; } //! Routine which gets a HealthImaging image set's metadata. /*! \param dataStoreID: The HealthImaging data store ID. \param imageSetID: The HealthImaging image set ID. \param versionID: The HealthImaging image set version ID, ignored if empty. \param outputFilePath: The path where the metadata will be stored as gzipped json. \param clientConfig: Aws client configuration. \\return bool: Function succeeded. */ bool AwsDoc::Medical_Imaging::getImageSetMetadata(const Aws::String &dataStoreID, const Aws::String &imageSetID, const Aws::String &versionID, const Aws::String &outputFilePath, const Aws::Client::ClientConfiguration &clientConfig) { Aws::MedicalImaging::Model::GetImageSetMetadataRequest request; request.SetDatastoreId(dataStoreID); request.SetImageSetId(imageSetID); if (!versionID.empty()) { request.SetVersionId(versionID); } Aws::MedicalImaging::MedicalImagingClient client(clientConfig); Aws::MedicalImaging::Model::GetImageSetMetadataOutcome outcome = client.GetImageSetMetadata( request); if (outcome.IsSuccess()) { std::ofstream file(outputFilePath, std::ios::binary); auto &metadata = outcome.GetResult().GetImageSetMetadataBlob(); file << metadata.rdbuf(); } else { std::cerr << "Failed to get image set metadata: " << outcome.GetError().GetMessage() << std::endl; } return outcome.IsSuccess(); }

イメージフレームをダウンロード、デコード、検証します。

bool AwsDoc::Medical_Imaging::downloadDecodeAndCheckImageFrames( const Aws::String &dataStoreID, const Aws::Vector<ImageFrameInfo> &imageFrames, const Aws::String &outDirectory, const Aws::Client::ClientConfiguration &clientConfiguration) { Aws::Client::ClientConfiguration clientConfiguration1(clientConfiguration); clientConfiguration1.executor = Aws::MakeShared<Aws::Utils::Threading::PooledThreadExecutor>( "executor", 25); Aws::MedicalImaging::MedicalImagingClient medicalImagingClient( clientConfiguration1); Aws::Utils::Threading::Semaphore semaphore(0, 1); std::atomic<size_t> count(imageFrames.size()); bool result = true; for (auto &imageFrame: imageFrames) { Aws::MedicalImaging::Model::GetImageFrameRequest getImageFrameRequest; getImageFrameRequest.SetDatastoreId(dataStoreID); getImageFrameRequest.SetImageSetId(imageFrame.mImageSetId); Aws::MedicalImaging::Model::ImageFrameInformation imageFrameInformation; imageFrameInformation.SetImageFrameId(imageFrame.mImageFrameId); getImageFrameRequest.SetImageFrameInformation(imageFrameInformation); auto getImageFrameAsyncLambda = [&semaphore, &result, &count, imageFrame, outDirectory]( const Aws::MedicalImaging::MedicalImagingClient *client, const Aws::MedicalImaging::Model::GetImageFrameRequest &request, Aws::MedicalImaging::Model::GetImageFrameOutcome outcome, const std::shared_ptr<const Aws::Client::AsyncCallerContext> &context) { if (!handleGetImageFrameResult(outcome, outDirectory, imageFrame)) { std::cerr << "Failed to download and convert image frame: " << imageFrame.mImageFrameId << " from image set: " << imageFrame.mImageSetId << std::endl; result = false; } count--; if (count <= 0) { semaphore.ReleaseAll(); } }; // End of 'getImageFrameAsyncLambda' lambda. medicalImagingClient.GetImageFrameAsync(getImageFrameRequest, getImageFrameAsyncLambda); } if (count > 0) { semaphore.WaitOne(); } if (result) { std::cout << imageFrames.size() << " image files were downloaded." << std::endl; } return result; } bool AwsDoc::Medical_Imaging::decodeJPHFileAndValidateWithChecksum( const Aws::String &jphFile, uint32_t crc32Checksum) { opj_image_t *outputImage = jphImageToOpjBitmap(jphFile); if (!outputImage) { return false; } bool result = true; if (!verifyChecksumForImage(outputImage, crc32Checksum)) { std::cerr << "The checksum for the image does not match the expected value." << std::endl; std::cerr << "File :" << jphFile << std::endl; result = false; } opj_image_destroy(outputImage); return result; } opj_image * AwsDoc::Medical_Imaging::jphImageToOpjBitmap(const Aws::String &jphFile) { opj_stream_t *inFileStream = nullptr; opj_codec_t *decompressorCodec = nullptr; opj_image_t *outputImage = nullptr; try { std::shared_ptr<opj_dparameters> decodeParameters = std::make_shared<opj_dparameters>(); memset(decodeParameters.get(), 0, sizeof(opj_dparameters)); opj_set_default_decoder_parameters(decodeParameters.get()); decodeParameters->decod_format = 1; // JP2 image format. decodeParameters->cod_format = 2; // BMP image format. std::strncpy(decodeParameters->infile, jphFile.c_str(), OPJ_PATH_LEN); inFileStream = opj_stream_create_default_file_stream( decodeParameters->infile, true); if (!inFileStream) { throw std::runtime_error( "Unable to create input file stream for file '" + jphFile + "'."); } decompressorCodec = opj_create_decompress(OPJ_CODEC_JP2); if (!decompressorCodec) { throw std::runtime_error("Failed to create decompression codec."); } int decodeMessageLevel = 1; if (!setupCodecLogging(decompressorCodec, &decodeMessageLevel)) { std::cerr << "Failed to setup codec logging." << std::endl; } if (!opj_setup_decoder(decompressorCodec, decodeParameters.get())) { throw std::runtime_error("Failed to setup decompression codec."); } if (!opj_codec_set_threads(decompressorCodec, 4)) { throw std::runtime_error("Failed to set decompression codec threads."); } if (!opj_read_header(inFileStream, decompressorCodec, &outputImage)) { throw std::runtime_error("Failed to read header."); } if (!opj_decode(decompressorCodec, inFileStream, outputImage)) { throw std::runtime_error("Failed to decode."); } if (DEBUGGING) { std::cout << "image width : " << outputImage->x1 - outputImage->x0 << std::endl; std::cout << "image height : " << outputImage->y1 - outputImage->y0 << std::endl; std::cout << "number of channels: " << outputImage->numcomps << std::endl; std::cout << "colorspace : " << outputImage->color_space << std::endl; } } catch (const std::exception &e) { std::cerr << e.what() << std::endl; if (outputImage) { opj_image_destroy(outputImage); outputImage = nullptr; } } if (inFileStream) { opj_stream_destroy(inFileStream); } if (decompressorCodec) { opj_destroy_codec(decompressorCodec); } return outputImage; } //! Template function which converts a planar image bitmap to an interleaved image bitmap and //! then verifies the checksum of the bitmap. /*! * @param image: The OpenJPEG image struct. * @param crc32Checksum: The CRC32 checksum. * @return bool: Function succeeded. */ template<class myType> bool verifyChecksumForImageForType(opj_image_t *image, uint32_t crc32Checksum) { uint32_t width = image->x1 - image->x0; uint32_t height = image->y1 - image->y0; uint32_t numOfChannels = image->numcomps; // Buffer for interleaved bitmap. std::vector<myType> buffer(width * height * numOfChannels); // Convert planar bitmap to interleaved bitmap. for (uint32_t channel = 0; channel < numOfChannels; channel++) { for (uint32_t row = 0; row < height; row++) { uint32_t fromRowStart = row / image->comps[channel].dy * width / image->comps[channel].dx; uint32_t toIndex = (row * width) * numOfChannels + channel; for (uint32_t col = 0; col < width; col++) { uint32_t fromIndex = fromRowStart + col / image->comps[channel].dx; buffer[toIndex] = static_cast<myType>(image->comps[channel].data[fromIndex]); toIndex += numOfChannels; } } } // Verify checksum. boost::crc_32_type crc32; crc32.process_bytes(reinterpret_cast<char *>(buffer.data()), buffer.size() * sizeof(myType)); bool result = crc32.checksum() == crc32Checksum; if (!result) { std::cerr << "verifyChecksumForImage, checksum mismatch, expected - " << crc32Checksum << ", actual - " << crc32.checksum() << std::endl; } return result; } //! Routine which verifies the checksum of an OpenJPEG image struct. /*! * @param image: The OpenJPEG image struct. * @param crc32Checksum: The CRC32 checksum. * @return bool: Function succeeded. */ bool AwsDoc::Medical_Imaging::verifyChecksumForImage(opj_image_t *image, uint32_t crc32Checksum) { uint32_t channels = image->numcomps; bool result = false; if (0 < channels) { // Assume the precision is the same for all channels. uint32_t precision = image->comps[0].prec; bool signedData = image->comps[0].sgnd; uint32_t bytes = (precision + 7) / 8; if (signedData) { switch (bytes) { case 1 : result = verifyChecksumForImageForType<int8_t>(image, crc32Checksum); break; case 2 : result = verifyChecksumForImageForType<int16_t>(image, crc32Checksum); break; case 4 : result = verifyChecksumForImageForType<int32_t>(image, crc32Checksum); break; default: std::cerr << "verifyChecksumForImage, unsupported data type, signed bytes - " << bytes << std::endl; break; } } else { switch (bytes) { case 1 : result = verifyChecksumForImageForType<uint8_t>(image, crc32Checksum); break; case 2 : result = verifyChecksumForImageForType<uint16_t>(image, crc32Checksum); break; case 4 : result = verifyChecksumForImageForType<uint32_t>(image, crc32Checksum); break; default: std::cerr << "verifyChecksumForImage, unsupported data type, unsigned bytes - " << bytes << std::endl; break; } } if (!result) { std::cerr << "verifyChecksumForImage, error bytes " << bytes << " signed " << signedData << std::endl; } } else { std::cerr << "'verifyChecksumForImage', no channels in the image." << std::endl; } return result; }

リソースをクリーンアップします。

bool AwsDoc::Medical_Imaging::cleanup(const Aws::String &stackName, const Aws::String &dataStoreId, const Aws::Client::ClientConfiguration &clientConfiguration) { bool result = true; if (!stackName.empty() && askYesNoQuestion( "Would you like to delete the stack " + stackName + "? (y/n)")) { std::cout << "Deleting the image sets in the stack." << std::endl; result &= emptyDatastore(dataStoreId, clientConfiguration); printAsterisksLine(); std::cout << "Deleting the stack." << std::endl; result &= deleteStack(stackName, clientConfiguration); } return result; } bool AwsDoc::Medical_Imaging::emptyDatastore(const Aws::String &datastoreID, const Aws::Client::ClientConfiguration &clientConfiguration) { Aws::MedicalImaging::Model::SearchCriteria emptyCriteria; Aws::Vector<Aws::String> imageSetIDs; bool result = false; if (searchImageSets(datastoreID, emptyCriteria, imageSetIDs, clientConfiguration)) { result = true; for (auto &imageSetID: imageSetIDs) { result &= deleteImageSet(datastoreID, imageSetID, clientConfiguration); } } return result; }
注記

には他にもがあります GitHub。AWS コード例リポジトリ で全く同じ例を見つけて、設定と実行の方法を確認してください。

JavaScript
SDK for JavaScript (v3)

index.js - ステップをオーケストレーションします。

// 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 { loadState, saveState } from "./state-steps.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 - リソースをデプロイします。

// 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 - DICOM ファイルをコピーします。

// 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 - データストアへのインポートを開始します。

// 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 - 画像セット IDs。

// 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 - イメージフレーム IDs。

// 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 - イメージフレームを検証します。AWS HealthImaging Pixel Data Verification ライブラリが検証に使用されました。

// 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 - 破棄されたリソース。

// 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, }, );
注記

には他にもがあります GitHub。AWS コード例リポジトリ で全く同じ例を見つけて、設定と実行の方法を確認してください。

Python
SDK for Python (Boto3)

必要なリソースを含む AWS CloudFormation スタックを作成します。

def deploy(self): """ Deploys prerequisite resources used by the scenario. The resources are defined in the associated `setup.yaml` AWS CloudFormation script and are deployed as a CloudFormation stack, so they can be easily managed and destroyed. """ print("\t\tLet's deploy the stack for resource creation.") stack_name = q.ask("\t\tEnter a name for the stack: ", q.non_empty) data_store_name = q.ask( "\t\tEnter a name for the Health Imaging Data Store: ", q.non_empty ) account_id = boto3.client("sts").get_caller_identity()["Account"] with open( "../../../../workflows/healthimaging_image_sets/resources/cfn_template.yaml" ) as setup_file: setup_template = setup_file.read() print(f"\t\tCreating {stack_name}.") stack = self.cf_resource.create_stack( StackName=stack_name, TemplateBody=setup_template, Capabilities=["CAPABILITY_NAMED_IAM"], Parameters=[ { "ParameterKey": "datastoreName", "ParameterValue": data_store_name, }, { "ParameterKey": "userAccountID", "ParameterValue": account_id, }, ], ) print("\t\tWaiting for stack to deploy. This typically takes a minute or two.") waiter = self.cf_resource.meta.client.get_waiter("stack_create_complete") waiter.wait(StackName=stack.name) stack.load() print(f"\t\tStack status: {stack.stack_status}") outputs_dictionary = { output["OutputKey"]: output["OutputValue"] for output in stack.outputs } self.input_bucket_name = outputs_dictionary["BucketName"] self.output_bucket_name = outputs_dictionary["BucketName"] self.role_arn = outputs_dictionary["RoleArn"] self.data_store_id = outputs_dictionary["DatastoreID"] return stack

DICOM ファイルを Amazon S3 インポートバケットにコピーします。

def copy_single_object(self, key, source_bucket, target_bucket, target_directory): """ Copies a single object from a source to a target bucket. :param key: The key of the object to copy. :param source_bucket: The source bucket for the copy. :param target_bucket: The target bucket for the copy. :param target_directory: The target directory for the copy. """ new_key = target_directory + "/" + key copy_source = {"Bucket": source_bucket, "Key": key} self.s3_client.copy_object( CopySource=copy_source, Bucket=target_bucket, Key=new_key ) print(f"\n\t\tCopying {key}.") def copy_images( self, source_bucket, source_directory, target_bucket, target_directory ): """ Copies the images from the source to the target bucket using multiple threads. :param source_bucket: The source bucket for the images. :param source_directory: Directory within the source bucket. :param target_bucket: The target bucket for the images. :param target_directory: Directory within the target bucket. """ # Get list of all objects in source bucket. list_response = self.s3_client.list_objects_v2( Bucket=source_bucket, Prefix=source_directory ) objs = list_response["Contents"] keys = [obj["Key"] for obj in objs] # Copy the objects in the bucket. for key in keys: self.copy_single_object(key, source_bucket, target_bucket, target_directory) print("\t\tDone copying all objects.")

DICOM ファイルを Amazon S3 データストアのにインポートします。

class MedicalImagingWrapper: """Encapsulates Amazon HealthImaging functionality.""" def __init__(self, medical_imaging_client, s3_client): """ :param medical_imaging_client: A Boto3 Amazon MedicalImaging client. :param s3_client: A Boto3 S3 client. """ self.medical_imaging_client = medical_imaging_client self.s3_client = s3_client @classmethod def from_client(cls): medical_imaging_client = boto3.client("medical-imaging") s3_client = boto3.client("s3") return cls(medical_imaging_client, s3_client) def start_dicom_import_job( self, data_store_id, input_bucket_name, input_directory, output_bucket_name, output_directory, role_arn, ): """ Routine which starts a HealthImaging import job. :param data_store_id: The HealthImaging data store ID. :param input_bucket_name: The name of the Amazon S3 bucket containing the DICOM files. :param input_directory: The directory in the S3 bucket containing the DICOM files. :param output_bucket_name: The name of the S3 bucket for the output. :param output_directory: The directory in the S3 bucket to store the output. :param role_arn: The ARN of the IAM role with permissions for the import. :return: The job ID of the import. """ input_uri = f"s3://{input_bucket_name}/{input_directory}/" output_uri = f"s3://{output_bucket_name}/{output_directory}/" try: job = self.medical_imaging_client.start_dicom_import_job( jobName="examplejob", datastoreId=data_store_id, dataAccessRoleArn=role_arn, inputS3Uri=input_uri, outputS3Uri=output_uri, ) except ClientError as err: logger.error( "Couldn't start DICOM import job. Here's why: %s: %s", err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return job["jobId"]

DICOM インポートジョブによって作成された画像セットを取得します。

class MedicalImagingWrapper: """Encapsulates Amazon HealthImaging functionality.""" def __init__(self, medical_imaging_client, s3_client): """ :param medical_imaging_client: A Boto3 Amazon MedicalImaging client. :param s3_client: A Boto3 S3 client. """ self.medical_imaging_client = medical_imaging_client self.s3_client = s3_client @classmethod def from_client(cls): medical_imaging_client = boto3.client("medical-imaging") s3_client = boto3.client("s3") return cls(medical_imaging_client, s3_client) def get_image_sets_for_dicom_import_job(self, datastore_id, import_job_id): """ Retrieves the image sets created for an import job. :param datastore_id: The HealthImaging data store ID :param import_job_id: The import job ID :return: List of image set IDs """ import_job = self.medical_imaging_client.get_dicom_import_job( datastoreId=datastore_id, jobId=import_job_id ) output_uri = import_job["jobProperties"]["outputS3Uri"] bucket = output_uri.split("/")[2] key = "/".join(output_uri.split("/")[3:]) # Try to get the manifest. retries = 3 while retries > 0: try: obj = self.s3_client.get_object( Bucket=bucket, Key=key + "job-output-manifest.json" ) body = obj["Body"] break except ClientError as error: retries = retries - 1 time.sleep(3) try: data = json.load(body) expression = jmespath.compile("jobSummary.imageSetsSummary[].imageSetId") image_sets = expression.search(data) except json.decoder.JSONDecodeError as error: image_sets = import_job["jobProperties"] return image_sets def get_image_set(self, datastore_id, image_set_id, version_id=None): """ Get the properties of an image set. :param datastore_id: The ID of the data store. :param image_set_id: The ID of the image set. :param version_id: The optional version of the image set. :return: The image set properties. """ try: if version_id: image_set = self.medical_imaging_client.get_image_set( imageSetId=image_set_id, datastoreId=datastore_id, versionId=version_id, ) else: image_set = self.medical_imaging_client.get_image_set( imageSetId=image_set_id, datastoreId=datastore_id ) except ClientError as err: logger.error( "Couldn't get image set. Here's why: %s: %s", err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return image_set

画像セットの画像フレーム情報を取得します。

class MedicalImagingWrapper: """Encapsulates Amazon HealthImaging functionality.""" def __init__(self, medical_imaging_client, s3_client): """ :param medical_imaging_client: A Boto3 Amazon MedicalImaging client. :param s3_client: A Boto3 S3 client. """ self.medical_imaging_client = medical_imaging_client self.s3_client = s3_client @classmethod def from_client(cls): medical_imaging_client = boto3.client("medical-imaging") s3_client = boto3.client("s3") return cls(medical_imaging_client, s3_client) def get_image_frames_for_image_set(self, datastore_id, image_set_id, out_directory): """ Get the image frames for an image set. :param datastore_id: The ID of the data store. :param image_set_id: The ID of the image set. :param out_directory: The directory to save the file. :return: The image frames. """ image_frames = [] file_name = os.path.join(out_directory, f"{image_set_id}_metadata.json.gzip") file_name = file_name.replace("/", "\\\\") self.get_image_set_metadata(file_name, datastore_id, image_set_id) try: with gzip.open(file_name, "rb") as f_in: doc = json.load(f_in) instances = jmespath.search("Study.Series.*.Instances[].*[]", doc) for instance in instances: rescale_slope = jmespath.search("DICOM.RescaleSlope", instance) rescale_intercept = jmespath.search("DICOM.RescaleIntercept", instance) image_frames_json = jmespath.search("ImageFrames[][]", instance) for image_frame in image_frames_json: checksum_json = jmespath.search( "max_by(PixelDataChecksumFromBaseToFullResolution, &Width)", image_frame, ) image_frame_info = { "imageSetId": image_set_id, "imageFrameId": image_frame["ID"], "rescaleIntercept": rescale_intercept, "rescaleSlope": rescale_slope, "minPixelValue": image_frame["MinPixelValue"], "maxPixelValue": image_frame["MaxPixelValue"], "fullResolutionChecksum": checksum_json["Checksum"], } image_frames.append(image_frame_info) return image_frames except TypeError: return {} except ClientError as err: logger.error( "Couldn't get image frames for image set. Here's why: %s: %s", err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise return image_frames def get_image_set_metadata( self, metadata_file, datastore_id, image_set_id, version_id=None ): """ Get the metadata of an image set. :param metadata_file: The file to store the JSON gzipped metadata. :param datastore_id: The ID of the data store. :param image_set_id: The ID of the image set. :param version_id: The version of the image set. """ try: if version_id: image_set_metadata = self.medical_imaging_client.get_image_set_metadata( imageSetId=image_set_id, datastoreId=datastore_id, versionId=version_id, ) else: image_set_metadata = self.medical_imaging_client.get_image_set_metadata( imageSetId=image_set_id, datastoreId=datastore_id ) with open(metadata_file, "wb") as f: for chunk in image_set_metadata["imageSetMetadataBlob"].iter_chunks(): if chunk: f.write(chunk) except ClientError as err: logger.error( "Couldn't get image metadata. Here's why: %s: %s", err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise

イメージフレームをダウンロード、デコード、検証します。

class MedicalImagingWrapper: """Encapsulates Amazon HealthImaging functionality.""" def __init__(self, medical_imaging_client, s3_client): """ :param medical_imaging_client: A Boto3 Amazon MedicalImaging client. :param s3_client: A Boto3 S3 client. """ self.medical_imaging_client = medical_imaging_client self.s3_client = s3_client @classmethod def from_client(cls): medical_imaging_client = boto3.client("medical-imaging") s3_client = boto3.client("s3") return cls(medical_imaging_client, s3_client) def get_pixel_data( self, file_path_to_write, datastore_id, image_set_id, image_frame_id ): """ Get an image frame's pixel data. :param file_path_to_write: The path to write the image frame's HTJ2K encoded pixel data. :param datastore_id: The ID of the data store. :param image_set_id: The ID of the image set. :param image_frame_id: The ID of the image frame. """ try: image_frame = self.medical_imaging_client.get_image_frame( datastoreId=datastore_id, imageSetId=image_set_id, imageFrameInformation={"imageFrameId": image_frame_id}, ) with open(file_path_to_write, "wb") as f: for chunk in image_frame["imageFrameBlob"].iter_chunks(): f.write(chunk) except ClientError as err: logger.error( "Couldn't get image frame. Here's why: %s: %s", err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise def download_decode_and_check_image_frames( self, data_store_id, image_frames, out_directory ): """ Downloads image frames, decodes them, and uses the checksum to validate the decoded images. :param data_store_id: The HealthImaging data store ID. :param image_frames: A list of dicts containing image frame information. :param out_directory: A directory for the downloaded images. :return: True if the function succeeded; otherwise, False. """ total_result = True for image_frame in image_frames: image_file_path = f"{out_directory}/image_{image_frame['imageFrameId']}.jph" self.get_pixel_data( image_file_path, data_store_id, image_frame["imageSetId"], image_frame["imageFrameId"], ) image_array = self.jph_image_to_opj_bitmap(image_file_path) crc32_checksum = image_frame["fullResolutionChecksum"] # Verify checksum. crc32_calculated = zlib.crc32(image_array) image_result = crc32_checksum == crc32_calculated print( f"\t\tImage checksum verified for {image_frame['imageFrameId']}: {image_result }" ) total_result = total_result and image_result return total_result @staticmethod def jph_image_to_opj_bitmap(jph_file): """ Decode the image to a bitmap using an OPENJPEG library. :param jph_file: The file to decode. :return: The decoded bitmap as an array. """ # Use format 2 for the JPH file. params = openjpeg.utils.get_parameters(jph_file, 2) print(f"\n\t\tImage parameters for {jph_file}: \n\t\t{params}") image_array = openjpeg.utils.decode(jph_file, 2) return image_array

リソースをクリーンアップします。

def destroy(self, stack): """ Destroys the resources managed by the CloudFormation stack, and the CloudFormation stack itself. :param stack: The CloudFormation stack that manages the example resources. """ print(f"\t\tCleaning up resources and {stack.name}.") data_store_id = None for oput in stack.outputs: if oput["OutputKey"] == "DatastoreID": data_store_id = oput["OutputValue"] if data_store_id is not None: print(f"\t\tDeleting image sets in data store {data_store_id}.") image_sets = self.medical_imaging_wrapper.search_image_sets( data_store_id, {} ) image_set_ids = [image_set["imageSetId"] for image_set in image_sets] for image_set_id in image_set_ids: self.medical_imaging_wrapper.delete_image_set( data_store_id, image_set_id ) print(f"\t\tDeleted image set with id : {image_set_id}") print(f"\t\tDeleting {stack.name}.") stack.delete() print("\t\tWaiting for stack removal. This may take a few minutes.") waiter = self.cf_resource.meta.client.get_waiter("stack_delete_complete") waiter.wait(StackName=stack.name) print("\t\tStack delete complete.") class MedicalImagingWrapper: """Encapsulates Amazon HealthImaging functionality.""" def __init__(self, medical_imaging_client, s3_client): """ :param medical_imaging_client: A Boto3 Amazon MedicalImaging client. :param s3_client: A Boto3 S3 client. """ self.medical_imaging_client = medical_imaging_client self.s3_client = s3_client @classmethod def from_client(cls): medical_imaging_client = boto3.client("medical-imaging") s3_client = boto3.client("s3") return cls(medical_imaging_client, s3_client) def search_image_sets(self, datastore_id, search_filter): """ Search for image sets. :param datastore_id: The ID of the data store. :param search_filter: The search filter. For example: {"filters" : [{ "operator": "EQUAL", "values": [{"DICOMPatientId": "3524578"}]}]}. :return: The list of image sets. """ try: paginator = self.medical_imaging_client.get_paginator("search_image_sets") page_iterator = paginator.paginate( datastoreId=datastore_id, searchCriteria=search_filter ) metadata_summaries = [] for page in page_iterator: metadata_summaries.extend(page["imageSetsMetadataSummaries"]) except ClientError as err: logger.error( "Couldn't search image sets. Here's why: %s: %s", err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return metadata_summaries def delete_image_set(self, datastore_id, image_set_id): """ Delete an image set. :param datastore_id: The ID of the data store. :param image_set_id: The ID of the image set. """ try: delete_results = self.medical_imaging_client.delete_image_set( imageSetId=image_set_id, datastoreId=datastore_id ) except ClientError as err: logger.error( "Couldn't delete image set. Here's why: %s: %s", err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise
注記

には他にもがあります GitHub。AWS コード例リポジトリ で全く同じ例を見つけて、設定と実行の方法を確認してください。