Dynamic Analysis Algorithm Updates via Centralized Cloud Server
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Solution Overview
Problem
Dynamic imaging provides a vast amount of information but challenges exist in ensuring homogeneity and accuracy of analysis across different medical facilities due to variations in dynamic analysis algorithms and data management systems, leading to inconsistencies in medical services.
Innovation Solution
A dynamic analysis system that modifies and updates algorithms based on anonymized data sets from multiple sources, ensuring consistent and accurate analysis results by integrating data from various hospitals and tests, using a dynamic analysis server that receives and processes data sets from different collection devices to refine the analysis algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If dynamic analysis algorithms are stored in each image management device at individual hospitals, then local analysis capability is improved, but homogeneity and consistency of analysis results across different facilities deteriorate
Solution Approach 1:
A cloud-based server acts as an intermediary between individual hospitals' image management devices and the dynamic analysis algorithms. The server receives dynamic images from various hospitals, performs centralized analysis using updated algorithms, and returns results to the requesting facilities. This mediator approach enables local devices to maintain analysis capability while ensuring homogeneous results across all facilities through centralized algorithm management.
Solution Approach 2:
The patent merges the dynamic analysis algorithm storage and execution function from individual hospital devices to a centralized cloud server. By combining the computational resources and algorithm management at a central location, the system achieves both local analysis capability (through cloud access) and result homogeneity (through unified algorithm versioning and updates).
2Measurement precision
If on-premises image management devices are upgraded to reflect new dynamic analysis algorithms, then analysis accuracy is improved, but implementation time and cost increase
Solution Approach 1:
The cloud server performs preliminary actions by pre-processing and updating dynamic analysis algorithms centrally before they are needed by individual hospitals. When new algorithms are developed or improved, the server automatically receives, processes, and prepares the updated algorithms in advance, making them immediately available to all connected facilities without requiring simultaneous upgrades at each location.
Solution Approach 2:
The system implements feedback mechanisms where the cloud server continuously monitors and receives updated dynamic analysis algorithms from algorithm providers. This feedback loop enables automatic algorithm updates and distribution to all connected image management devices, ensuring all facilities access the latest accurate algorithms without manual intervention or extended implementation timelines.
3Measurement precision
If more dynamic image data is collected from multiple sources, then analysis accuracy is improved, but data management complexity and processing time increase
Solution Approach 1:
The cloud-based server is designed with universal functionality to handle diverse data sources including dynamic images from multiple hospitals, various imaging modalities, and different formats. The system provides a unified interface and standardized processing pipeline that can accommodate multiple data sources without increasing complexity at individual facility levels, centralizing the complexity management at the server.
Data Source
AI summary
A recording medium storing a computer-readable program for modifying a dynamic analysis algorithm that performs dynamic analysis to a dynamic image, the program causing a computer to perform: a process of receiving, from a first data collection device, a first data set that is anonymized and includes a first dynamic image obtained by dynamic imaging with radiation on a first subject and information obtained by a first test other than the dynamic imaging on the first subject; a process of receiving, from a second data collection device, a second data set that is anonymized and includes a second dynamic image obtained by dynamic imaging with radiation on a second subject and information obtained by a second test other than the dynamic imaging on the second subject; and a process of modifying the dynamic analysis algorithm based on the first data set and the second data set.