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Medical Imaging Server for DICOM

Product
The name of the base system (platform): Microsoft Azure
Date of the premiere of the system: November, 2020.
Branches: Pharmaceutics, medicine, health care
Technology: Systems of video analytics,  PACS

2020: Start of open DICOM server for storage and transfer of medical pictures

In the middle of November, 2020 Microsoft started DICOM server open source for storage and transfer of medical pictures. The tool under the name Medical Imaging Server for DICOM is useful to developers for transfer of medical images in a cloud and integration of metadata of images into clinical data in the FHIR system using DICOM Cast technology.

To receive the maximum advantage of cloud computing, it is necessary not only to move data to the existing user formats, but also to use the correct tools for structurization of data. The FHIR system creates the standard of exchange of clinical data in a cloud, helping to reduce costs for postprocessing and to accelerate machine learning.

Microsoft provided open DICOM server for storage and transfer of medical pictures

DICOM is an international standard of transfer, storage, processing and information display about medical images. DICOM is used in most the medical organizations for diagnostics along with clinical data, but data of DICOM were serviced and controlled irrespective of clinical data of FHIR. Microsoft developers tried to overcome this gap, having released the new tools integrating the DICOM and FHIR systems in a cloud.

According to in Microsoft, the solution Medical Imaging Server for DICOM simplifies process of data reception of medical visualization in a cloud. Developers can unroll the open source software in read minutes and configure group of the Azure resources to include cloud data management of images. At the same time along with loading of images through DICOM server the structured metadata from these files contact the clinical data which are stored in the FHIR system. Consolidation of these data in a cloud facilitates creation of cohorts for a research, provides long observation of patients with creation of a feedback loop and also gives the chance for external archiving and data backup.[1]

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