Workflow Management Module for Medical Image Data Integration
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Solution Overview
Problem
Current systems for managing and analyzing medical images in clinical and research settings face challenges in efficiently processing, storing, and utilizing large volumes of data, particularly in translating research findings into clinical practices, due to complexities in regulatory compliance, data privacy, and the need for structured and reproducible workflows.
Innovation Solution
An integrated system comprising a workflow management module, image and data repository, and cloud storage, which includes pre-processing engines, data integration, and analysis modules to manage, anonymize, and analyze medical images, utilizing AI and deep learning algorithms, and a blockchain ledger for traceability and security, facilitating efficient data sharing and regulatory compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large volumes of medical images and data are collected and stored for research and clinical use, then the quantity and diversity of data increase, but data management complexity and storage requirements increase
Solution Approach 1:
The system segments data management into distinct functional modules: data integration module for receiving and initial processing, data management module for parsing and organizing, pre-processing engine for automated algorithmic processing, and data utilization module for distribution. This modular segmentation handles large data volumes by dividing management tasks into manageable components.
Solution Approach 2:
The workflow management module acts as an intermediary between image-generating devices, storage devices, and the image and data repository. It coordinates data flow, manages collation, and handles distribution, thereby simplifying the complexity of direct interactions between multiple systems and components.
2Productivity
If automated algorithms and AI processing are applied to images and data, then processing efficiency and analysis capability improve, but system complexity and computational requirements increase
Solution Approach 1:
The pre-processing engine applies automated algorithms and AI processing to images and data before they are stored in the repository. This preliminary action prepares data in advance for future analysis, improving processing efficiency when data is retrieved and utilized, while encapsulating complexity within the pre-processing stage.
Solution Approach 2:
The system employs automated algorithms that operate independently to process, analyze, and prepare data without requiring manual intervention for each processing task. This self-service capability improves productivity by handling routine processing efficiently while maintaining manageable system complexity through automation.
3Reliability
If data is anonymized and processed for research purposes, then data privacy and regulatory compliance improve, but data utility and accessibility may be reduced
Solution Approach 1:
The system applies different processing treatments to different aspects of data: anonymization is applied to protect privacy while preserving the scientific utility of the data. The workflow management module coordinates this selective processing, ensuring that compliance requirements are met while maintaining data usefulness for research purposes.
4Reliability
If structured workflows and automated logging are implemented, then traceability and reproducibility improve, but processing time and operational overhead increase
Solution Approach 1:
Automated logging and workflow tracking operate continuously in the background without interrupting the main data processing and utilization workflows. This ensures traceability and reproducibility are maintained while minimizing additional processing time, as the logging functions run concurrently rather than sequentially.
Data Source
AI summary
Integrated systems for collecting, storing, and distribution of images acquired of subjects in a research or clinical environment are provided. The system includes an image and data repository including a plurality of images originating from one or more image-generating devices, data associated with the images, and data associated with imaged subjects; and a workflow management module in direct communication with the image and data repository and with the one or more image-generating devices and/or storage devices that store the images of the imaged subjects, the workflow management module being configured to transport the images directly from the one or more image-generating devices and/or storage devices to the image and data repository and to manage the collation and distribution of images, data associated with the raw images and the data associated with the imaged subjects in the image and data repository. The workflow management module includes a data integration module, a data management module, a pre-processing engine and a data utilization module.