This post has been republished via RSS; it originally appeared at: New blog articles in Microsoft Community Hub.
We are thrilled to announce the general availability of the Azure Health Data Services DICOM service with Data Lake Storage, a solution that enables teams to store, manage, and access their medical imaging data in the cloud. Whether you're involved in clinical operations, research endeavors, AI/ML model development, or any other facet of healthcare that involves medical imaging, the DICOM service can expand the possibilities of your imaging data and enable new workflows.
The DICOM service is available for teams to start using today with production imaging data. To get started, visit the Azure Health Data Services docs and follow the steps to Deploy the DICOM service with Data Lake Storage.
Who Can Benefit?
The DICOM service with Data Lake Storage is designed for any team that requires a robust and scalable cloud storage solution for their medical imaging data. Whether you're a healthcare institution migrating clinical and research data to the cloud, a development team in need of a scalable storage platform for imaging data, or an organization seeking to operationalize imaging data in AI/ML model development or secondary use scenarios, our DICOM service with Data Lake Storage is here to empower your endeavors.
Benefits of Azure Data Lake Storage
By integrating with Azure Data Lake Storage (ADLS Gen2), our DICOM service offers a myriad of benefits to healthcare teams:
- Scalable Storage: Enjoy performant, massively scalable storage capabilities that can effortlessly accommodate your growing imaging data assets.
- Data Governance: Take full control of your imaging data assets. Manage storage permissions, access controls, data replication strategies, backups, and more, ensuring compliance with global privacy standards.
- Direct Data Access: Seamlessly access your DICOM data through Azure Storage APIs, enabling efficient retrieval and manipulation of your valuable medical imaging assets. The DICOM service continues to provide DICOMweb APIs for storing, querying for, and retrieving imaging data.
- Ecosystem Integration: Leverage the entire ecosystem of tools surrounding ADLS, including AzCopy, Azure Storage Explorer, and Azure Storage Data Movement library, to help streamline your workflows and enhance productivity.
- Unlock New Possibilities: Unlock new analytics and AI/ML scenarios by integrating with services like Azure Synapse, Azure Databricks, Azure Machine Learning, and Microsoft Fabric, enabling you to extract deeper insights and drive innovation in healthcare.
Integration with Microsoft Fabric
As called out above, a key benefit of Azure Data Lake Storage is that it connects to Microsoft Fabric. Microsoft Fabric is an end-to-end, unified analytics platform that brings together all the data and analytics tools that organizations need to unlock the potential of their data and lay the foundation for AI scenarios. By using Microsoft Fabric, you can use the rich ecosystem of Azure services to perform advanced analytics and AI/ML with medical imaging data, such as building and deploying machine learning models, creating cohorts for clinical trials, and generating insights for patient care and outcomes.
Get Started Today
The DICOM service with Data Lake Storage is available for teams to start using today with production imaging data – and customers can expect to receive the same level of support and adherence consistent with the healthcare privacy standards that Azure Health Data Services is known for. Whether you're looking to enhance clinical operations, drive research breakthroughs, or unlock new AI-driven insights, the power of Azure Health Data Services can help you to achieve your goals.
To learn more about analytics with imaging data, see Get started using DICOM data in analytics workloads.
Pricing
With Azure Health Data Services, customers pay only for what they use. DICOM service customers incur storage costs for storage of the DICOM data and metadata used to operate the DICOM service as well as charges for API requests. The data lake storage model shifts most of the storage costs from Azure Health Data Services to Azure Data Lake Storage (where the .dcm files are stored).
For detailed pricing information, see Pricing - Azure Health Data Services and Azure Storage Data Lake Gen2 Pricing.