Fluorescence Image Processing Segmentation Contrast
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Solution Overview
Problem
Current fluorescence image processing techniques fail to effectively enhance images with low signal-to-noise ratio (SNR) resulting from rapid scanning and staining times, which are necessary for high-throughput digital pathology applications, leading to inadequate contrast for human operators.
Innovation Solution
A fluorescence image processing apparatus that segments images into areas of interest and background, measures and reduces background signals, and enhances the areas of interest, using noise in the background to improve contrast, while allowing for parallel processing and storage options for iterative quality improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If scanning and staining times are reduced to achieve high throughput, then productivity is improved, but signal-to-noise ratio deteriorates
Solution Approach 1:
The image is segmented into background areas and areas of interest based on intensity values. This allows different processing to be applied to different regions, enabling aggressive background suppression in low-signal regions while preserving detail in high-signal regions, thereby improving perceived SNR without requiring longer acquisition times
Solution Approach 2:
Different enhancement parameters are applied to different regions of the image based on local characteristics. Background areas receive strong suppression while areas of interest receive selective enhancement. This local differentiation allows the system to maintain high productivity with reduced acquisition times while recovering SNR through region-specific processing
2Manufacturing precision
If background signal is suppressed to enhance contrast, then image quality is improved, but useful information may be lost
Solution Approach 1:
The image is divided into background regions and foreground regions based on intensity thresholds. This segmentation allows the system to selectively suppress only the background regions while leaving the foreground regions (areas of interest) untouched or selectively enhanced, thereby improving contrast without losing useful information
Solution Approach 2:
Different processing operations are applied to different spatial regions based on their characteristics. Background regions undergo strong suppression while foreground regions receive minimal or selective processing. This local differentiation ensures that contrast enhancement does not result in loss of useful information from the areas of interest
Data Source
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AI summary
The present invention relates to a fluorescence image processing apparatus (100) for enhancing a fluorescence image. The fluorescence image processing apparatus (100) comprises an image segmentation unit (110), a background determination unit (120), a background reduction unit (130), and an image enhancement unit (140). It is porposed to first segment the background and the area of interest of a glass slide and to use this segmentation to enhance the contrast between both. By that, scanning and staining time can be reduced, while after enhancement the image data has still a comfortable contrast for the human operator.