Sample Container Image Recognition for Test Order Association
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Solution Overview
Problem
Current test management systems face inefficiencies in associating test results with test orders, particularly when manual identification methods like barcodes are used, leading to errors and inefficiencies in identifying subject information on sample containers.
Innovation Solution
A management system and method that utilize image processing to capture and match discrimination information on sample containers with pre-registered images, allowing for automatic association of test results with test orders without the need for manual identification units like barcodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual identification methods like barcodes are used to associate test results with test orders, then the process requires physical identification units attached to sample containers, but this increases device complexity and manual operation requirements
Solution Approach 1:
The invention extracts the identification information directly from the sample container's existing markings (handwritten names, printed labels) without requiring separate barcode stickers or identification units. The imaging device captures images of these existing markings, and the recognition unit extracts identification information from them, eliminating the need for physical barcode attachments while maintaining automated association capabilities
Solution Approach 2:
The system creates digital copies (images) of the discrimination information directly from the sample container surfaces. Instead of requiring physical barcode readers to scan attached identifiers, the system captures images of handwritten or printed information on the containers and processes these image copies to extract identification data, thereby eliminating complex physical identification units
2Reliability
If barcodes are manually attached to sample containers for identification, then subject information can be tracked, but this increases the time and labor required for the association process
Solution Approach 1:
The discrimination information (subject identification) is pre-marked on the sample containers by the subjects themselves or by collection personnel before the testing process begins. This preliminary marking eliminates the need for time-consuming barcode attachment procedures later, as the identification information is already present on the containers when they reach the testing stage
Solution Approach 2:
Subjects themselves provide the discrimination information by writing or printing their identification directly on the sample containers. This self-service approach eliminates the need for manual barcode attachment by hospital staff, reducing labor time while maintaining reliable association between samples and test orders through the pre-present identification information
3Device complexity
If handwritten discrimination information is used on sample containers, then no additional identification units are needed, but the accuracy of reading and matching this information becomes difficult
Solution Approach 1:
Instead of attempting to directly read and interpret handwritten characters (which is error-prone), the system captures high-quality images of the discrimination information on the sample containers and processes these image copies. The recognition unit extracts identification information from the captured images using image processing techniques, which are more accurate than direct human reading and eliminate misinterpretation of handwritten text
Solution Approach 2:
The invention replaces manual visual inspection and reading of handwritten information with an automated image-based recognition system. The imaging device captures the discrimination information, and the recognition unit uses image processing algorithms to extract and match the identification data, substituting the mechanical human reading process with an automated optical system that achieves higher precision
Data Source
AI summary
A management system including at least one processor, wherein the processor is configured to acquire a captured image obtained by imaging an outer surface of each of plural sample containers which contains a sample and in which discrimination information for discriminating a subject from whom the sample is collected is given to the outer surface, and associate a test result related to the sample contained in each of the sample containers with a test order in which information of a discrimination image including the discrimination information is registered in advance for each subject, based on the captured image and the test order.