Fluorescence Image Analyzer Bright Point Pattern Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In fluorescence image analysis, accurately determining whether a sample is positive or negative for chromosomal abnormalities is challenging due to the presence of various positive patterns, which can lead to determination omissions and reduced accuracy.
Innovation Solution
A fluorescence image analyzer that processes and displays bright point patterns from fluorescence images, allowing users to select and associate positive patterns with measurement items or labeling reagents, and provides information on the number and proportion of abnormal and normal cells, thereby improving the accuracy of determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple positive patterns are present in fluorescence image analysis, then the comprehensiveness of detection is improved, but the complexity of determination increases and accuracy decreases due to determination omissions
Solution Approach 1:
The patent segments the complex determination process into distinct components: automatic pattern recognition by the processing unit, visual display of multiple positive patterns on the display unit, and selective operator confirmation. This segmentation reduces determination omissions by ensuring all patterns are systematically considered while maintaining manageable complexity through automated assistance.
Solution Approach 2:
The patent implements feedback mechanisms where the processing unit automatically recognizes patterns and presents them to the operator via the display unit. The operator can then confirm or correct the automatic recognition results. This feedback loop improves determination accuracy by combining automated pattern detection with human expertise while reducing the cognitive burden on operators.
2Productivity
If automatic analysis is used to process fluorescence images, then productivity is improved, but measurement precision may be degraded due to inability to handle atypical patterns
Solution Approach 1:
The processing unit performs preliminary automatic recognition of positive patterns from fluorescence images, pre-processing the data and presenting multiple candidate patterns to the operator. This preliminary action maintains high productivity by automating the initial analysis while preserving measurement precision by allowing operator verification of atypical or uncertain patterns before final determination.
Solution Approach 2:
The system combines automatic pattern recognition capabilities with operator review functionality in a unified analysis platform. The processing unit handles routine pattern identification while the display unit presents results for operator confirmation, creating a multi-functional system that maintains both high throughput and accurate recognition of diverse patterns including atypical cases.
3Reliability
If all positive patterns are displayed for selection, then determination completeness is improved, but ease of operation decreases due to increased user workload
Solution Approach 1:
The processing unit performs complete pattern recognition and displays all detected positive patterns on the display unit, even though the operator may not need to manually verify each one. This excessive action ensures determination completeness by presenting all candidates while maintaining ease of operation because the operator can quickly review and confirm results without performing exhaustive manual analysis of every pattern.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enhances the accuracy of determining whether a sample is positive or negative by clearly displaying and managing positive patterns, reducing the likelihood of omissions and improving user recognition of cell information.
Implementation Method 1
a sample (10) that includes a plurality of cells in which target portions are labeled with fluorescent dyes... a light source (120 to 123) configured to apply light to the sample (10)... an imaging unit (160) configured to take a fluorescence image of each of the cells by which fluorescence is generated by applying the light
Data Source
AI summary
Disclosed is a fluorescence image analyzer for measuring and analyzing a sample that includes a plurality of cells in which target portions are labeled with fluorescent dyes, and the fluorescence image analyzer includes a light source configured to apply light to the sample; an imaging unit configured to take a fluorescence image of each of the cells by which fluorescence is generated by applying the light; a processing unit configured to process the fluorescence image having been taken; and a display unit. The processing unit obtains a bright point pattern of fluorescence in the fluorescence image, causes the display unit to display a plurality of positive patterns that are previously associated with at least one of a measurement item or a labeling reagent, and causes the display unit to display information of at least one of the number of abnormal cells included in the sample, a proportion of the number of the abnormal cells, the number of normal cells included in the sample, and a proportion of the normal cells, based on the bright point pattern having been obtained and the plurality of positive patterns.