At Dicom Systems, our technology has always been designed to function as a “universal adapter” for enterprise imaging, with interoperability as the guiding principle. To achieve this vision of nimble interoperability, the AI Conductor was designed as a Linux-base appliance, managed via a simple browser environment. By leveraging the industry standards discussed above, our platform integrates seamlessly with hospital information systems, including PACS, RIS and EHR.
In a 6-step process, images and other health information flow through the AI router platform as illustrated below:
The AI router receives DICOM images or other imaging-related objects and scans all metadata as they are coming in
AI router flags any predetermined metadata signaling that a set of imaging objects are candidates for one or several AI algorithms, some of which may be on prem, and others in a cloud. For cloud-based algorithms, the AI router platform can be programmed to automatically de-identify pixel and metadata in order to maintain strict HIPAA compliance.
The AI router signals to the appropriate docker that a study has been identified for further processing by the algorithm
The AI router pushes metadata via QIDO-RS and pixel data via WADO-RS to the appropriate docker
The docker analyzes the data and returns a result back to the AI router via STOW-RS
The AI router receives the results from the docker, translates the result into the appropriate standard expected by the end-user system: DICOM-SR to PACS and/or dictation system, HL7 or FHIR to EHR/EMR, DICOM overlays to the PACS