Cell Image Analysis Device Feature Correlation Selection
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Solution Overview
Problem
The challenge lies in efficiently selecting images of cells with predetermined feature values from a large number of images in biological and medical analysis, particularly when analyzing interactions within or between cells, as existing methods are labor-intensive and inefficient.
Innovation Solution
An analysis device and method that acquire, process, and select cell images based on calculated feature values and correlations, utilizing a cell-image acquiring unit, feature value calculating unit, correlation calculating unit, and image selecting unit to identify and extract relevant images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing techniques are used to analyze cell interactions, then measurement precision is improved, but device complexity increases due to the large number of images requiring processing
Solution Approach 1:
The patent extracts and calculates specific feature values from cell images, such as fluorescence intensity, area, and shape characteristics. By focusing on these extracted features rather than processing all image data, the system achieves precise measurement of cell interactions while reducing the complexity of image processing requirements
Solution Approach 2:
The patent transforms image data into quantitative parameter representations (feature values) that can be systematically analyzed. By changing the representation from raw images to calculated parameters, the system enables efficient correlation analysis between different cellular components without requiring complex image processing of all captured images
2Measurement precision
If correlations between multiple cellular components are calculated, then measurement precision is improved, but loss of time increases due to the large number of images requiring analysis
Solution Approach 1:
The patent performs preliminary calculation of feature values for each cell image before conducting correlation analysis. By pre-processing and extracting relevant features in advance, the system enables efficient correlation calculations between different cellular components without requiring time-consuming analysis of all raw image data
Solution Approach 2:
The patent creates simplified representations (feature value copies) of cellular components from original images. These copied feature values can be rapidly compared and correlated without requiring access to or processing of the original large-size images, significantly reducing analysis time while maintaining measurement precision
3Measurement precision
If a large number of cell images are captured to analyze cellular interactions, then measurement precision is improved, but ease of operation deteriorates due to the difficulty of selecting relevant images
Solution Approach 1:
The patent implements automatic selection of relevant cell images based on calculated feature values and correlation analysis. The system performs self-service by autonomously identifying and selecting images that meet predetermined criteria without requiring manual intervention, thereby maintaining high measurement precision while significantly improving ease of operation
Solution Approach 2:
The patent replaces manual image selection (mechanical operation) with automated computational selection based on feature value correlations. This substitution eliminates the need for researchers to manually review and select relevant images from large datasets, making the operation efficient and accessible while maintaining scientific rigor
Data Source
AI summary
An analysis device configured to analyze a correlation between feature values in a cell in response to a stimulus includes: a cell-image acquiring unit configured to acquire a plurality of cell images in which the cell that is stimulated is captured; a feature value calculating unit configured to calculate a feature value for constituent elements that form the cell, based on the plurality of cell images acquired by the cell-image acquiring unit; a correlation calculating unit configured to use the feature value calculated by the feature value calculating unit and to calculate correlations between the constituent elements; a correlation selecting unit configured to select a first correlation from the correlations calculated by the correlation calculating unit; and an image selecting unit configured to select a first cell image from the plurality of cell images that are captured, based on the first correlation that is selected.