Medical Image Inference Routing With Multi-Model Reliability
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing computer-aided diagnosis systems lack the ability to utilize multiple information processing apparatuses for improved medical image analysis, as they do not support the selection and utilization of multiple trained models for enhanced reliability.
Innovation Solution
An information processing system that includes an information terminal capable of selecting and transmitting medical image data to one or more information processing apparatuses, each equipped with an inference unit, allowing these apparatuses to make inferences using trained models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single information processing apparatus is used for inference, then the system structure is simple, but the reliability and effectiveness of medical image analysis are limited
Solution Approach 1:
The system segments the inference function across multiple independent information processing apparatuses (130, 132, 134), each capable of performing inference independently. This segmentation allows the system to distribute the analytical workload and improve reliability through diversity of inference sources without requiring a completely new system architecture
Solution Approach 2:
The system merges the inference results from multiple information processing apparatuses through the selection unit (406) at the information terminal (110). By combining multiple inference outputs and selecting the most appropriate result, the system achieves enhanced reliability while maintaining manageable structural complexity through centralized result integration
2Measurement precision
If multiple information processing apparatuses are used for inference, then the accuracy and efficiency are improved, but the system complexity increases
Solution Approach 1:
Each information processing apparatus (130, 132, 134) is equipped with specialized inference units trained for specific medical image analysis tasks. This local quality specialization allows each apparatus to excel at particular diagnostic functions, improving overall accuracy while maintaining individual apparatus simplicity
Solution Approach 2:
The selection unit (406) at the information terminal (110) acts as an intermediary that receives, evaluates, and selects from multiple inference results. This mediator coordinates the complex interactions between multiple apparatuses, managing the system complexity by providing a centralized decision-making layer that simplifies the user interface
3Reliability
If a plurality of information processing apparatuses are deployed, then the diagnostic support reliability is enhanced, but the difficulty of system management increases
Solution Approach 1:
The information terminal (110) serves multiple functions: acquiring medical image data, managing connections to multiple information processing apparatuses, receiving inference results, and presenting diagnostic support information. This universal device consolidates management responsibilities, improving ease of operation while supporting multiple apparatuses for enhanced reliability
Data Source
AI summary
An information processing system includes an information terminal configured to acquire medical image data from a medical image capturing apparatus, a plurality of information processing apparatuses each including an inference unit configured to make an inference about the medical image data by using a learned model, and a selection unit configured to select at least one information processing apparatus from the plurality of information processing apparatuses. The information terminal transmits the medical image data to the information processing apparatus selected by the selection unit, and the information processing apparatus selected by the selection unit makes an inference about the transmitted medical image data and transmits an inference result to the information terminal.