Algorithm Orchestration for Medical Imaging Diagnostics
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Solution Overview
Problem
The healthcare industry faces challenges in effectively integrating and orchestrating artificial intelligence (AI) and machine learning (ML) algorithms for medical imaging diagnostics, despite their potential for improved accuracy and precision, due to complexity in applying analytics to clinical care.
Innovation Solution
A centralized algorithm orchestration component that executes AI algorithms on medical images according to pre-defined workflows, managing workflow and model execution, and providing notification outputs, including status and metadata analysis, to facilitate integration of AI informatics into healthcare systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If AI algorithms are integrated into healthcare systems for medical imaging diagnostics, then diagnostic accuracy and precision are improved, but system complexity and difficulty in applying analytics to clinical care increase
Solution Approach 1:
The patent introduces a workflow engine as an intermediary component that mediates between AI algorithms and clinical workflows. This engine manages the complexity by providing a standardized interface for executing algorithms, handling metadata, and coordinating outputs, thereby enabling accurate diagnostics while reducing the operational complexity of integrating AI into healthcare systems.
Solution Approach 2:
The system segments the AI integration into distinct modular components: algorithm catalogs, workflow definitions, execution engines, and notification systems. This segmentation allows each component to be developed, tested, and maintained independently, reducing overall system complexity while maintaining high diagnostic precision through specialized algorithm modules.
2Adaptability or versatility
If multiple AI algorithms are deployed to analyze medical images, then diagnostic capabilities are enhanced, but workflow management complexity increases
Solution Approach 1:
The workflow engine provides universal functionality to manage multiple AI algorithms through a single standardized platform. It handles algorithm selection, execution, metadata processing, and output integration for diverse diagnostic tasks, thereby enhancing diagnostic capabilities across different modalities while avoiding the complexity of managing separate workflow systems for each algorithm.
Solution Approach 2:
The system performs preliminary actions by pre-defining workflows and algorithm selections before actual diagnostic tasks. Workflows are pre-configured with appropriate algorithms based on image types and diagnostic requirements, so that when diagnostics are needed, the complex selection and coordination of algorithms is already resolved, reducing real-time workflow management complexity.
3Measurement precision
If AI algorithms are applied to medical images, then diagnostic precision is improved, but computational resources and processing time requirements increase
Solution Approach 1:
The system applies partial action by selectively executing only the necessary AI algorithms based on the specific diagnostic task and image characteristics. The workflow engine evaluates requirements and deploys algorithms proportionally to the task needs rather than running all available algorithms, thereby maintaining high diagnostic precision for required analyses while reducing unnecessary computational resource consumption.
Data Source
AI summary
Techniques for orchestrating execution of algorithms on medical images according to pre-defined workflows and techniques for managing workflow and model execution are provided. In an embodiment, a system comprises a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components comprise an algorithm catalog that comprises algorithm information identifying algorithms available for processing medical images, the algorithm information comprising algorithm execution instructions for executing the algorithms as web-services; and an onboarding component that adds the algorithm information to the algorithm catalog in response to reception of the algorithm information via an onboarding user interface of an algorithm management application, wherein based on inclusion of the algorithm information in the algorithm catalog, the algorithms are made available for incorporating into workflows for executing the algorithms on the medical images.