Morphology-Aware Fluorescence Separation from Autofluorescence
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Solution Overview
Problem
In fluorescence and multi-marker immunostaining, accurate fluorescence separation between stained fluorescence and autofluorescence is challenging due to variations in autofluorescence spectra between pixels, leading to inconsistent results even in morphologically similar cells.
Innovation Solution
An information processing apparatus and system that utilizes an inference model incorporating morphological information and machine learning to separate fluorescence signals from biological samples, considering variations in fluorescent reagents and specimens, thereby improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional fluorescence separation methods are used, then the process is simple, but the separation accuracy between stained fluorescence and autofluorescence deteriorates due to spectral variations
Solution Approach 1:
The patent transforms the fluorescence separation problem from a simple spectral unmixing task to a multi-parameter analysis by incorporating morphological information (cell shape, size, texture) alongside spectral data. This parameter expansion enables more accurate differentiation between stained fluorescence and autofluorescence by considering both optical and structural characteristics of cells
Solution Approach 2:
The patent introduces morphological information as an intermediary element that mediates between the raw fluorescence image and the final separation result. By using cell morphology as an additional discriminator, the system can better distinguish true fluorescent signals from autofluorescence, especially in regions where spectral overlap occurs
2Reliability
If autofluorescence spectrum is extracted from unstained sections, then reference data is obtained, but variations between pixels still cause inconsistent separation results
Solution Approach 1:
The patent applies local quality analysis by evaluating morphological features at each pixel or small region independently. This allows the separation algorithm to adapt to local variations in cell morphology and autofluorescence characteristics, maintaining consistency across different regions of the tissue section
Solution Approach 2:
The patent adds a morphological dimension to the traditional spectral analysis. By incorporating spatial and structural information from histological images, the system transforms the problem from two-dimensional spectral unmixing to a multi-dimensional analysis that includes intensity, wavelength, shape, and texture features
3Adaptability or versatility
If more fluorescent dyes are used for multicoloring, then more information is obtained, but fluorescence separation accuracy deteriorates due to increased spectral overlap
Solution Approach 1:
The patent extends the separation space by incorporating morphological features alongside spectral data. This additional dimension provides extra discriminative power that becomes increasingly valuable as more fluorescent dyes are added and spectral overlap increases, enabling accurate separation in high-plex immunostaining applications
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 achieves more precise fluorescence separation by reducing noise and variations, enhancing image clarity and visibility of fluorescence regions, and improving user understanding of complex tissue images.
Implementation Method 1
a separation unit that separates a fluorescence signal derived from a fluorescent reagent from a fluorescence image on the basis of the fluorescence image of a biological sample containing a cell
Data Source
AI summary
Provided is an information processing apparatus that includes a separation unit that separates a fluorescence signal derived from a fluorescent reagent from a fluorescence image on the basis of the fluorescence image of a biological sample containing a cell, a reference spectrum derived from the biological sample or the fluorescent reagent, and morphological information of the cell.