Multi-Direction Illumination Microscopy for Rapid Sample Classification
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Solution Overview
Problem
In digital microscopy, there is a trade-off between speed and precision during sample screening, as high precision requires high magnification, leading to a time-consuming process of imaging multiple positions of the sample.
Innovation Solution
A method involving the training of a machine learning model using a training set of digital images acquired by illuminating the sample from multiple directions, allowing for faster and more accurate classification of samples without the need for high-magnification images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high magnification is used to improve classification precision, then measurement precision is improved, but productivity deteriorates due to the need to image a large number of individual positions
Solution Approach 1:
The patent transitions from analyzing single 2D images to analyzing 3D volumetric data by illuminating the sample from multiple directions (e.g., 0°, 45°, 90°, 135°) and combining the images. This dimensional expansion provides more comprehensive structural information for classification, enabling high precision at lower magnification and thus improving screening speed without sacrificing accuracy.
2Productivity
If the number of imaged positions is reduced to improve productivity, then screening speed is improved, but measurement precision deteriorates as the entire sample cannot be properly screened
Solution Approach 1:
By acquiring images from multiple illumination directions and synthesizing 3D volumetric information, the system gains enhanced depth perception and structural detail. This allows fewer 2D positions to suffice for complete sample characterization, as the multi-directional data compensates for the reduced spatial sampling, maintaining precision while improving speed.
Solution Approach 2:
The patent changes the illumination parameters (angle, direction, wavelength) to extract different structural information from the same sample region. By varying these parameters across multiple measurements, the system accumulates sufficient diagnostic information from fewer positional samples, resolving the speed-precision trade-off.
3Measurement precision
If conventional staining processes are used to improve classification accuracy, then measurement precision is improved, but object-affected harmful factors increase due to toxic chemicals
Solution Approach 1:
The patent replaces chemical staining mechanisms with physical optical measurement mechanisms. By using multi-directional illumination and 3D image synthesis, the system extracts structural and compositional information purely through optical means, eliminating the need for toxic staining chemicals while maintaining or improving classification accuracy through enhanced volumetric data.
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
This approach enables quick and reliable classification of samples with high speed and accuracy, reducing the need for computational power and avoiding the use of toxic chemicals typically required for staining processes.
Implementation Method 1
a training set of digital images of the sample is acquired by illuminating the sample from a plurality of directions and capturing a digital image for each of the plurality of directions
Data Source
AI summary
Devices and methods for training a machine learning model to analyze a sample are provided. An example method comprises: receiving a ground truth comprising a classification of at least one portion of a sample; acquiring a training set of digital images of the sample by illuminating the sample from a plurality of directions and capturing a digital image for each of the plurality of directions; and training the machine learning model to analyze the sample using the training set of digital images and the received ground truth. Further, a microscope system and a method for analyzing a sample is provided.