Virtual Stained Image Generation from Fluorescent Data
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Solution Overview
Problem
Current methods for converting fluorescent images into pseudo brightfield images do not accurately represent the biological sample as if it were subjected to traditional brightfield staining protocols like H&E, lacking sufficient contrast and detail for structural feature identification.
Innovation Solution
A method that maps fluorescent images into a new color space using nonlinear estimation models and sharpening transformations to generate a virtual stained image (VSI) resembling a brightfield image, incorporating feature-based and intensity-based registration techniques to simulate H&E staining.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fluorescent images are converted using simple color space reassignment, then the conversion process is simple and fast, but the resulting image lacks accurate representation of brightfield staining protocols and insufficient structural detail
Solution Approach 1:
The patent transforms fluorescent image data by applying parameter changes through a nonlinear estimation model that maps fluorescent signal intensities to virtual staining parameters. This involves transforming the relationship between fluorescent dye concentrations and observed intensities, then applying these transformed parameters to generate virtual H&E or other brightfield staining images, achieving accurate brightfield representation without simple color reassignment
Solution Approach 2:
The patent introduces an intermediary virtual staining parameter space between the fluorescent image data and the final brightfield image. Instead of direct conversion, the system first estimates virtual staining parameters that mediate the transformation, allowing accurate representation of brightfield staining protocols while maintaining the ability to generate different staining types from the same fluorescent input
2Loss of information
If traditional brightfield H&E staining is used, then structural and morphological details are clearly visible, but the method cannot provide molecular marker information and multi-plex biomarker detection
Solution Approach 1:
The patent merges multiple fluorescent biomarker channels into a unified virtual brightfield image that preserves both molecular information and structural details. By combining the molecular specificity of multiple fluorescent markers with the structural visualization of virtual H&E staining, the system simultaneously provides molecular marker information and clear morphological features in a single integrated image representation
Solution Approach 2:
The patent adds an additional dimension of information by overlaying molecular marker data onto the virtual brightfield image. The system creates a multi-dimensional representation where the third dimension contains molecular biomarker information that can be visualized through the virtual staining framework, allowing pathologists to access both structural and molecular data without sacrificing either
3Measurement precision
If fluorescent imaging is used alone, then molecular markers are accurately detected, but cell boundaries and internal features lack full resolution and contrast
Solution Approach 1:
The patent applies local quality enhancement by using the virtual staining parameters to selectively enhance different regions and structures within the image. The nonlinear estimation model allows for localized adjustment of staining intensities and contrasts, improving the visualization of cell boundaries and internal features in regions where they are most needed while preserving molecular marker accuracy in other areas
Data Source
AI summary
A method for generating a brightfield type image, which resembles a brightfield staining protocol of a biological sample, using fluorescent images is provided. The steps comprise acquiring two or more fluorescent images of a fixed area on a biological sample, mapping said fluorescent image into a brightfield color space, generating a brightfield image, and optionally applying a sharpening transformation correction. Also provided is an image analysis system for generating a brightfield type image of a biological sample using fluorescent images.