Medical Imaging Gateway Microservices for Firewall Deployment
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Solution Overview
Problem
Current medical imaging gateway management is cumbersome, requiring significant IT resources and is challenging to deploy and integrate due to lack of interoperability, making it difficult to transfer medical imaging data between health systems and cloud environments.
Innovation Solution
A cloud IoT-based framework with a medical imaging gateway deployed within a health system firewall, executing containerized code for processing medical image data, and a cloud platform with a container registry, utilizing secured messaging protocols and a flexible data-driven gateway edge system with a data and task orchestration engine for seamless data transfer and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current imaging gateway deployment methods are used, then data transfer between health systems and cloud can be achieved, but the deployment process becomes difficult and lengthy requiring significant IT resources
Solution Approach 1:
The gateway system is segmented into containerized microservices that can be independently deployed and managed. Each container encapsulates specific functionality, allowing modular installation and reducing overall deployment complexity while maintaining reliable data transfer capabilities.
Solution Approach 2:
A standardized interface layer is introduced between the health system and cloud platform, acting as an intermediary that simplifies integration. This interface handles protocol translation and data formatting, reducing the complexity of direct connections while ensuring reliable communication.
2Adaptability or versatility
If traditional gateway integration processes are used, then interoperability between systems can be achieved, but the integration becomes cumbersome and requires accounting for IT personnel capacity and roadmap
Solution Approach 1:
The gateway is designed with universal interfaces that support multiple communication protocols and data formats simultaneously. This multi-functionality allows the same gateway instance to integrate with various health systems and cloud platforms without requiring custom development, improving both interoperability and ease of deployment.
Solution Approach 2:
Integration configurations and interoperability settings are pre-configured within the container images before deployment. This preliminary action eliminates the need for complex post-deployment configuration and reduces integration efforts to simple container orchestration, making the system easier to operate while maintaining broad interoperability.
3Adaptability or versatility
If multiple gateways are deployed for different functions, then comprehensive data processing capability is achieved, but management of multiple gateways requires significant IT resources
Solution Approach 1:
Multiple gateway functions are merged into a single unified gateway instance through container orchestration. Different processing capabilities are implemented as separate containers managed by the same orchestration platform, allowing comprehensive data processing while simplifying management to a single deployment unit rather than multiple independent gateways.
Solution Approach 2:
The containerized gateway implements self-service capabilities including automatic health checks, self-healing mechanisms, and automated scaling. This reduces the need for manual IT intervention for routine management tasks, improving productivity while maintaining versatile data processing capabilities through automated container orchestration.
Data Source
AI summary
The disclosure provides a gateway edge system. The gateway edge system comprise (a) a clinical quality measure component comprising: a translation engine configured to receive data from a healthcare system, process the data to extract a plurality of elements, and translate the plurality of elements into a plurality of intermediate variables; and a clinical quality measure computation component configured to compute, based at least in part on the plurality of intermediate variables, a clinical quality measure indicative of whether a radiation dose is excessive, within a safe range, or inadequate; and (b) a data orchestration engine comprising a plurality of modules configured to receive and process the data according to a workflow and dynamically route the processed data to one or more entities that are in communication with the gateway edge system, and the gateway edge system is configured to be deployed within a firewall of the healthcare system.