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It provides a robust solution for removing or modifying sensitive patient information while preserving the integrity of medical imaging data.\n\n## Features\n\n- Anonymizes various DICOM elements including patient identifiers, names, dates, and addresses according to the [DICOM Standard](https://dicom.nema.org/medical/dicom/current/output/chtml/part15/chapter_E.html)\n- Customizable anonymization rules\n- Preserves DICOM data structure and integrity\n- Handles complex DICOM elements like sequences\n- Applicable in web-bowsers\n\n## Installation\n\nnpm install dicom-web-anonymizer\n\n## Usage\n\nHere's a basic example of how to use the DICOM Web Anonymizer:\n\n`import Anonymizer from 'dicom-web-anonymizer';`\\\n`import { data } from 'dcmjs';`\n\n// Create an instance of the Anonymizer \\\n`const anonymizer = new Anonymizer();`\n\n// Load your DICOM dataset\\\n`const dataset = data.DicomDict.fromDicomJson(/_ your DICOM JSON data _/);`\n\n// Anonymize the dataset\\\n`await anonymizer.anonymize(dataset);` \\\n\n// Your dataset is now anonymized \\\n`console.log(dataset);`\n\n## API Reference\n\n### `Anonymizer`\n\nThe main class for anonymizing DICOM datasets.\n\n#### Constructor\n\n- `constructor(options?: AnonymizerOptions)`\n\n#### Methods\n\n- `anonymize(dcmDict: data.DicomDict): Promise<void>`\n  Anonymizes the given DICOM dataset.\n\n### `Configuration`\n\nConfiguration options for the Anonymizer.\n\n- `protectedTags?: string[]`: List of DICOM tags to leave unchanged\n- `anonymizePrivateTags?: boolean`: Whether to anonymize (delete) private tags\n- `idPrefix?: string`: Prefix for anonymized IDs\n- `idSuffix?: string`: Suffix for anonymized IDs\n- `seed?: string`: Seed for the random number generator\n\n## License\n\nThis project is licensed under the MIT License - see the LICENSE file for details.\n","readmeFilename":"README.md"}