Blood Cell Image Classification for Count Verification
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Solution Overview
Problem
Existing blood cell counting and image classifying systems lack a reliable method for verifying the accuracy of blood cell counts, as quality control mechanisms are not sufficiently robust to confirm the correctness of blood cell classification results based on reference values.
Innovation Solution
A specimen processing system that integrates a blood cell counting apparatus and a blood cell image classifying apparatus, where the latter communicates with the former to receive count results, obtain image-based counts, store both types of results, and generate a quality control screen for comparison, outputting warnings when differences exceed predetermined ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a blood cell counting apparatus measures blood cells using optical information, then counting speed and efficiency are improved, but the reliability of classification accuracy cannot be sufficiently confirmed
Solution Approach 1:
The patent uses blood cell images as copies or references to verify the counting results. The image classifying apparatus creates visual representations of blood cells and compares them against the counting apparatus results, allowing manual verification without requiring physical re-counting, thus maintaining high productivity while improving reliability.
Solution Approach 2:
The system implements a feedback mechanism where the image classifying apparatus provides verification results back to the counting apparatus. The quality control screen displays comparison results between the two methods, and the system can automatically adjust or flag results that fall outside predetermined ranges, creating a closed-loop verification system.
2Reliability
If quality control is performed using existing schemes, then basic verification is maintained, but there is no reliable method to confirm correctness based on reference values
Solution Approach 1:
The patent replaces manual visual verification with an automated image-based verification system. Instead of relying on mechanical counting methods alone, the system uses optical imaging and computer processing to create a digital verification mechanism that can precisely compare and validate blood cell classification results against reference values.
Solution Approach 2:
The system changes the verification parameter from simple count numbers to visual image data. By transforming the verification process into an image-based comparison, the system can assess not only the quantity but also the quality and accuracy of blood cell classification, enabling more precise measurement against reference values.
3Measurement precision
If blood cell images are obtained and classified manually, then classification accuracy is improved, but the complexity of the verification process increases
Solution Approach 1:
The patent segments the verification process into distinct functional modules: an image acquiring unit for capturing blood cell images, an image classifying unit for automated classification, and a quality control unit for comparison and verification. This segmentation allows each component to perform its specific function independently, reducing overall system complexity while maintaining high accuracy.
Solution Approach 2:
The image classifying apparatus serves multiple functions: it acquires blood cell images, classifies them automatically, compares results with the counting apparatus, and generates quality control screens. By making the system multi-functional, the patent reduces the need for separate verification devices, thereby reducing overall system complexity while improving measurement precision.
Data Source
AI summary
A specimen processing system comprising: a blood cell counting apparatus; and a blood cell image classifying apparatus, wherein the blood cell image classifying apparatus comprises a controller to carry out operations, comprising: receiving a plurality of first count results of a predetermined type of the blood cell by the blood cell counting apparatus; obtaining a plurality of second count results of the predetermined type of the blood cell on the basis of the blood cell image; storing the plurality of the first count results and the second count results; reading at least one of the first count results, and at least one of the second count results obtained from a blood specimen corresponding to the first count result; generating and outputting a quality control screen on the basis of the read first count result and the read second count result. A blood cell image classifying apparatus is also disclosed.