Virtual Staining of Tissue Samples via Neural Network
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Solution Overview
Problem
Current methods for staining biological samples are time-consuming, damage biomolecules, and do not provide real-time evaluation, limiting immediate feedback in critical settings like operating rooms, and fail to offer detailed molecular information.
Innovation Solution
A computer-implemented method using an artificial neural network trained with image pairs of stained and unstained tissue samples to generate virtually stained images, allowing for the prediction of stain binding without actual staining, utilizing hyperspectral and color imaging modes to create detailed virtual staining without damaging the samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If traditional staining methods are used, then contrast and highlighting of tissue features are improved, but time consumption and sample damage increase
Solution Approach 1:
The patent creates a virtual copy of the staining process through computational imaging. Instead of physically staining the tissue sample, the system captures multiple spectral images and synthesizes a virtual stained image that replicates the appearance of traditionally stained samples. This copying approach eliminates the need for time-consuming physical staining while preserving tissue integrity and reducing preparation time from hours to minutes.
Solution Approach 2:
The patent replaces the mechanical/chemical staining system with an optical-computational system. Rather than using chemical dyes that bind to tissue components, the system uses spectral imaging to capture intrinsic optical properties of tissues and algorithms to generate virtual stains. This substitution eliminates chemical reagents and extended processing times while achieving comparable diagnostic contrast.
2Illumination intensity
If traditional staining methods are used, then tissue feature visualization is improved, but biomolecule damage and loss of molecular information increase
Solution Approach 1:
The system creates a virtual representation of stained tissue without exposing the actual sample to damaging chemical stains. By capturing spectral information that reflects intrinsic tissue properties and synthesizing virtual stain appearances, the method preserves biomolecules in their native state while still providing the visual contrast needed for diagnostic evaluation.
Solution Approach 2:
The tissue sample itself provides the necessary information through its intrinsic spectral properties. Rather than requiring external chemical agents to create contrast, the system exploits the natural optical characteristics of different tissue components across multiple wavelengths. The tissue's own spectral signature enables the generation of virtual stains that highlight features without external intervention that could cause damage.
3Measurement precision
If sophisticated laser systems are used for virtual staining, then H&E virtual image generation is improved, but device complexity and cost increase
Solution Approach 1:
The patent employs a standard widefield fluorescence microscope that can perform multiple functions: capturing spectral images across different wavelengths and generating various virtual stain types (H&E, trichrome, etc.) from the same hardware platform. This universal approach eliminates the need for specialized laser systems while achieving comparable virtual staining quality through computational methods applied to broadband spectral data.
Solution Approach 2:
The system achieves high-quality virtual H&E images by varying spectral parameters (wavelength bands) rather than requiring complex laser parameters. By capturing images across a broad spectrum using filter sets and applying appropriate computational transformations, the system generates accurate virtual stains without the need for sophisticated pulsed fiber lasers or complex temporal-spatial laser control.
4Measurement precision
If point scanning systems are used, then spectral image acquisition is improved, but imaging speed decreases
Solution Approach 1:
The system uses periodic spectral filtering to capture images across multiple wavelengths. Instead of scanning point-by-point through spectral dimensions, the system rapidly cycles through different filter bands, capturing a full spectral dataset for the entire field of view simultaneously at each wavelength. This periodic filtering approach maintains spectral precision while achieving whole-field imaging speeds that are orders of magnitude faster than point scanning.
Data Source
AI summary
Systems and methods for generating virtually stained images of unstained samples are provided. According to an aspect of the invention, a method includes accessing an image training dataset including a plurality of image pairs. Each image pair includes a first image of an unstained first tissue sample, and a second image acquired when the first tissue sample is stained. The method also includes accessing a set of parameters for an artificial neural network, wherein the set of parameters includes weights associated with artificial neurons within the artificial neural network; training the artificial neural network by using the image training dataset and the set of parameters to adjust the weights; accessing a third image of a second tissue sample that is unstained; using the trained artificial neural network to generate a virtually stained image of the second tissue sample from the third image; and outputting the virtually stained image.