Fluorescence Image Analysis for Chromosomal Abnormality Detection
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Solution Overview
Problem
Current fluorescence in situ hybridization (FISH) methods rely heavily on human interpretation, which is prone to error due to the complexity of distinguishing between typical and non-typical chromosomal abnormal patterns, and the accuracy of determining bright spot patterns depends on the operator's skill, leading to inconsistencies in diagnosing chromosomal abnormalities.
Innovation Solution
A fluorescence image analyzing apparatus and method that captures and processes fluorescence images of cells labeled with fluorescent dyes, using a processing unit to select reference patterns and generate information for determining whether a bright spot pattern is abnormal, thereby reducing reliance on operator interpretation and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual interpretation by operators is used to determine bright spot patterns, then flexibility in handling various chromosomal abnormal patterns is maintained, but measurement precision and reliability deteriorate due to operator skill variations and subjective judgment
Solution Approach 1:
The patent creates digital copies of chromosomal abnormality patterns (reference patterns) that can be stored and reused. These reference patterns are digital representations of typical chromosomal abnormalities that can be automatically compared against test samples, eliminating the need for operators to memorize patterns while maintaining consistent diagnostic criteria across different users and time periods.
Solution Approach 2:
The patent replaces the manual visual inspection and subjective judgment mechanism with an automated image processing and pattern recognition system. The system uses computational algorithms to compare fluorescence images against stored reference patterns, substituting human cognitive processes with mechanical computation to achieve consistent, objective measurements.
2Adaptability or versatility
If operators must memorize multiple positive and negative patterns for different probes, then comprehensive detection capability is achieved, but ease of operation deteriorates due to the burden of memorization and training
Solution Approach 1:
The system enables self-service operation where the apparatus automatically performs pattern recognition and diagnostic determination without requiring operators to have expert knowledge. The automated system handles the complex pattern matching and interpretation tasks, allowing operators to simply initiate the analysis and receive results, thereby making the sophisticated FISH method accessible to users with varying levels of expertise.
Solution Approach 2:
The patent creates a universal reference pattern library that can be used across different probe types and measurement scenarios. The system is designed to handle multiple measurement items (different chromosomal abnormalities, different probes) using a common framework of stored reference patterns, making the system versatile without requiring separate expertise for each specific probe or abnormality type.
3Productivity
If automated image processing is implemented, then productivity is improved by reducing manual analysis time, but device complexity increases due to the need for processing units and reference pattern storage
Solution Approach 1:
The patent performs preliminary actions by pre-storing reference patterns of chromosomal abnormalities in the system memory before actual diagnostic use. These reference patterns are prepared in advance and organized for quick retrieval, so that during actual operation, the system can rapidly compare test images against the pre-prepared reference library without needing to perform complex pattern recognition from scratch, thereby achieving high-speed automated analysis.
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 chromosomal abnormalities by automatically analyzing fluorescence images and comparing them to reference patterns, eliminating the need for operators to memorize multiple patterns and reducing subjective judgment, thus improving the reliability of chromosomal abnormality detection.
Implementation Method 1
a light source (120 to 123) that emits light to a sample (10) including a plurality of cells labeled with a fluorescent dye at a target site
Implementation Method 2
an imaging unit (160) that captures a fluorescence image of each of the cells that emit fluorescence by being irradiated with the light
Data Source
Figure 1
Figure 2A~2D
Figure 3
AI summary
Disclosed is a fluorescence image analyzing apparatus (1) including a light source (120, 121, 122, 123) that emits light to a sample (10) including a plurality of cells labeled with a fluorescent dye at a target site, an imaging unit (160) that captures a fluorescence image of each of the cells that emit fluorescence by being irradiated with the light, a fluorescence image of the cell, and a processing unit (11) that processes the fluorescence image captured by the imaging unit (160) to acquire a bright spot pattern of fluorescence in the fluorescence image. The processing unit (11) selects a reference pattern corresponding to a measurement item of the sample (10) from a plurality of reference patterns corresponding to a plurality of measurement items and generates information used for determination of the sample (10) based on the bright spot pattern of fluorescence in the fluorescence image and the selected reference pattern.