Biofluorescence Image Separation Accuracy Evaluation
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Solution Overview
Problem
Current color separation technologies in biofluorescence imaging fail to completely remove autofluorescence components with high fluorescence luminance, leading to deterioration in image accuracy and separation accuracy, particularly evident in the case of red blood cells.
Innovation Solution
An information processing device and biological sample observation system that includes a separation unit to separate stained and autofluorescence components, a generation unit to calculate and visualize separation accuracy for each pixel, and an evaluation unit to identify outlier pixels, thereby improving image and separation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color separation technology using least squares method or non-negative matrix factorization is used, then stained fluorescence can be separated from autofluorescence, but autofluorescence components with high fluorescence luminance cannot be completely removed
Solution Approach 1:
The patent introduces a feedback mechanism by calculating separation accuracy for each pixel based on the difference between the original specimen image and the separated image, then using this accuracy information to identify and handle outlier pixels. This feedback loop allows the system to continuously improve separation accuracy by detecting and correcting errors in the separation process, thereby resolving the contradiction between separation accuracy and image accuracy.
Solution Approach 2:
The patent performs preliminary calculation of separation accuracy and identification of outlier pixels before final image output. By pre-identifying pixels where separation may have failed (outliers), the system can apply corrective measures in advance, such as excluding these pixels from further analysis or applying alternative separation methods, thus preventing accuracy deterioration in the final image.
2Productivity
If conventional color separation methods are applied, then processing can be completed efficiently, but separation accuracy deteriorates due to incomplete removal of high luminance autofluorescence
Solution Approach 1:
The patent implements partial action by selectively processing only the pixels that are identified as outliers rather than re-processing the entire image. The system calculates separation accuracy for all pixels but applies corrective measures only to the subset of pixels where separation failed, thus maintaining high processing efficiency while improving separation accuracy for problematic regions.
3Device complexity
If separation is performed without evaluating pixel-level accuracy, then processing is simpler and faster, but image accuracy and separation precision deteriorate
Solution Approach 1:
The patent segments the image processing into distinct stages: initial separation, pixel-level accuracy calculation, outlier identification, and selective correction. By dividing the processing into these modular segments, the system can evaluate pixel-level accuracy without substantially increasing overall complexity, as each segment performs a specific function and can be implemented using standard computational techniques.
Data Source
AI summary
An information processing device according to an aspect of the present disclosure includes a fluorescence separation unit (131A) that is an example of a separation unit that separates at least one of a stained fluorescence component or an autofluorescence component from a fluorescence component obtained from a specimen image of fluorescent staining, a generation unit (131B) that calculates separation accuracy for each of pixels from a difference between the specimen image and an image after separation obtained by separating at least one of the stained fluorescence component or the autofluorescence component from the fluorescence component, and generates a separation accuracy image indicating the separation accuracy for each of the pixels, and an evaluation unit (131C) that identifies a pixel including an outlier of the separation accuracy from the separation accuracy image.