Blood Cell Imaging Abnormality Detection via Segmented Analysis
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Solution Overview
Problem
Existing sample imaging apparatuses cannot accurately distinguish between abnormalities in stained samples and imaging section issues, leading to incorrect analysis results when staining or light intensity abnormalities occur.
Innovation Solution
A sample imaging apparatus equipped with an imaging section and a staining abnormality detector to generate cell images and detect abnormalities related to staining, as well as an imaging abnormality detector to identify issues with the imaging process, allowing for precise classification and correction of blood cell images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single detection system is used to identify all abnormalities in blood cell images, then the device complexity is reduced, but the measurement precision and ability to distinguish between staining abnormalities and imaging section issues deteriorates
Solution Approach 1:
The detection system is segmented into two independent functional modules: a staining abnormality detector that analyzes staining quality using color information from blood cell images, and an imaging abnormality detector that identifies imaging section issues using focus information. This segmentation allows each module to specialize in detecting specific types of abnormalities, thereby improving measurement precision while maintaining manageable device complexity through modular design.
2Measurement precision
If multiple detection modules are added to distinguish between staining and imaging abnormalities, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The imaging apparatus integrates multiple detection functions into a unified system that processes blood cell images through shared components. The staining abnormality detector and imaging abnormality detector both utilize the same blood cell image data, with the staining detector using color information and the imaging detector using focus information. This multi-functional approach allows precise abnormality identification while avoiding redundant hardware, thereby limiting the increase in device complexity.
3Productivity
If staining abnormalities are not detected, then the analysis process continues without interruption, but the reliability of blood cell classification results deteriorates due to undetected staining issues
Solution Approach 1:
The staining abnormality detector performs preliminary detection of staining quality before the blood cell classification process proceeds. By analyzing color information in blood cell images and comparing it against predefined standards, the system identifies staining abnormalities in advance. When abnormalities are detected, the system can interrupt or flag the classification process, ensuring that unreliable results from poorly stained samples do not compromise overall analysis reliability.
Data Source
AI summary
A sample imaging apparatus comprising: an imaging section for imaging a stained sample including a stained cell to generate a cell image relating to the stained cell included in the stained sample; and a staining abnormality detector for detecting an abnormality relating to staining of the stained sample on the basis of the cell image generated by the imaging section, is disclosed. A sample imaging apparatus comprising: an imaging section for imaging a stained sample to generate a cell image relating to a cell included in the stained sample; and an imaging abnormality detector for detecting an abnormality relating to the imaging section on the basis of the cell image generated by the imaging section, is also disclosed.