Distributed Medical Image Workflow Dispatcher
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current medical image management systems are inflexible and do not support seamless access and sharing of medical images across a multi-facility enterprise, making it difficult to share and analyze data effectively.
Innovation Solution
A distributed medical digital image computing environment that uses a medical imaging cloud computing model to administer medical images by receiving a medical image business object, selecting appropriate clinical workflows, and processing the images using computational units, enabling intelligent analytic execution and secure routing of resultant images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a distributed medical digital image computing environment is implemented, then adaptability and ease of access to medical images across multiple facilities is improved, but device complexity increases
Solution Approach 1:
The system segments the medical image computing environment into multiple distributed computational units that can independently process images. Each unit can be deployed across different facilities, enabling flexible access and processing while maintaining system manageability through modular architecture.
Solution Approach 2:
The computational units are designed with universal interfaces and standardized protocols that allow them to function across multiple healthcare facilities. The system provides multi-functional capabilities including image processing, storage, and retrieval through a unified platform that adapts to different facility requirements.
2Productivity
If intelligent analytic execution of workflows is implemented, then productivity and data analysis capability is improved, but device complexity increases
Solution Approach 1:
The system pre-configures computational units with analytical workflows and processing algorithms before medical images are submitted. This preliminary preparation enables rapid processing and analysis when images are received, improving productivity without requiring complex real-time decision-making infrastructure.
Solution Approach 2:
The computational units autonomously execute analytical workflows and make processing decisions based on pre-configured rules and algorithms. This self-service capability eliminates the need for complex centralized control systems, improving productivity while managing complexity through automated decision-making.
3Reliability
If secure routing and processing of medical images is implemented, then reliability and security are improved, but device complexity increases
Solution Approach 1:
The system introduces intermediary components including workflow dispatchers and routing mechanisms that manage image transmission and processing securely. These intermediaries handle authentication, authorization, and secure data transmission, improving reliability and security while maintaining manageable system complexity through specialized intermediary layers.
Data Source
AI summary
Administering medical digital images including receiving a medical image business object representing a transaction carrying out a type of service request made by a health care provider; selecting, in dependence upon workflow selection rules and the attributes of the medical image business object, one or more clinical workflows to process the medical image according to the transaction; and processing the medical image of the request with the clinical workflows, thereby creating a resultant business object and resultant medical image including selecting, by the workflow dispatcher in dependence upon metadata for computational units in the distributed medical digital image computing environment, particular computational units in the distributed medical digital image computing environment to perform particular services of the one or more clinical workflows, deploying the particular services to the particular computational units, and executing the services on the computational units upon which they are deployed.