Image Recognition for Sample Container Subject Identification
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Solution Overview
Problem
Current test management systems face inefficiencies in associating test results with test orders, particularly when multiple sample containers from different subjects are processed together, and there is a need for a method that does not rely on identification units like barcodes.
Innovation Solution
A management system and method that uses image recognition to associate test results with test orders by imaging the outer surfaces of sample containers and boundary containers, which may include dummy containers, to identify subject and group information, allowing for efficient grouping and result association without manual labeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual barcode attachment and reading is used to associate test results with test orders, then identification accuracy is maintained, but productivity and efficiency deteriorate
Solution Approach 1:
The patent replaces manual mechanical operations (barcode attachment and reading) with an automated image recognition system. The management device captures images of sample containers and automatically recognizes subject information, eliminating the need for manual barcode handling while maintaining accurate association between test results and test orders.
Solution Approach 2:
The system enables self-service by allowing the management device to automatically perform the entire association process without human intervention. The device independently captures images, recognizes information, and associates test results with test orders, freeing operators from repetitive manual tasks.
2Measurement precision
If barcodes are attached to sample containers for identification, then subject identification accuracy is improved, but the complexity of the process and materials required increases
Solution Approach 1:
The patent extracts the identification function from physical barcodes and implements it through image recognition. By removing the barcode medium while retaining the identification capability through direct imaging of subject information on container labels, the system simplifies the overall process while maintaining accuracy.
3Productivity
If multiple sample containers from different test orders are collectively set in a test device, then productivity is improved, but the risk of misassociation between test results and test orders increases
Solution Approach 1:
The patent applies segmentation by dividing the batch processing into individually identifiable units. Each sample container is imaged and its subject information is recognized separately, creating distinct identification records for each container even when processed collectively, thereby preventing misassociation.
Solution Approach 2:
The system implements feedback by capturing images of each sample container, recognizing the subject information, and using this recognized information to accurately associate test results with the corresponding test orders. This closed-loop verification ensures reliable association even during batch processing.
Data Source
AI summary
A management system including a processor, the processor is configured to acquire an image obtained by imaging an outer surface of each of plural sample containers and a boundary container, the sample container containing a sample and in which subject information of a subject from whom the sample is collected is given to the outer surface, the boundary container in which group boundary information indicating a boundary between plural groups of subjects is given to the outer surface, recognize the subject information and the group boundary information based on the image, and associate a test result related to the sample contained in each of the sample containers with a test order which includes the subject information and in which the group is divided corresponding to the group boundary information, based on a result of the recognition and the test order.