Multispectral Microscope Image Registration via Spectral Crosstalk
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing multispectral microscope systems struggle to account for mechanical misalignment due to thermal drift during actual measurements, as traditional methods require explicit calibration and cannot adapt to drift occurring during sample measurement.
Innovation Solution
A multispectral microscope system that includes a processor to determine spatial correlation between images captured in different spectral channels based on spectral crosstalk, allowing for on-line registration of images and accounting for thermal drift.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional calibration methods are used for image registration, then manufacturing precision is improved, but adaptability to thermal drift during measurements deteriorates
Solution Approach 1:
The patent applies preliminary action by embedding a reference sample with known spatial correlations into the measurement setup before actual measurements. This reference sample enables the system to pre-determine transformation parameters that can be applied during measurements to correct for thermal drift, thus combining manufacturing precision with adaptability to environmental changes
Solution Approach 2:
The patent implements feedback by continuously monitoring the spatial correlation between detector elements using the reference sample during measurements. When thermal drift causes misalignment, the system detects this through the reference sample and automatically adjusts the transformation parameters to maintain accurate image registration, thereby adapting to thermal drift in real-time
2Stability of the object's composition
If athermal design with invar materials is used, then stability against thermal expansion is improved, but manufacturing cost and complexity increase
Solution Approach 1:
The patent replaces the mechanical athermal design approach with a computational solution. Instead of using expensive invar materials and complex athermal mechanical structures, the system uses software-based image registration that calculates transformation parameters from reference sample data to compensate for thermal expansion, thereby achieving thermal stability without the associated manufacturing complexity and cost
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting the transformation parameters (translation, rotation, scaling) based on measured spatial correlations from the reference sample. This allows the system to adapt to thermal expansion without requiring physically stable athermal construction, simplifying the mechanical design while maintaining registration accuracy
3Manufacturing precision
If explicit calibration step is performed, then manufacturing precision is improved, but measurement time increases
Solution Approach 1:
The patent merges the calibration process with the measurement process by using the reference sample during actual measurements. The reference sample remains in the field of view throughout, allowing the system to continuously determine transformation parameters without interrupting the measurement workflow, thus eliminating separate calibration steps while maintaining registration accuracy
Solution Approach 2:
The patent ensures continuity of useful action by performing image registration calculations continuously during measurements using the reference sample. Instead of performing calibration once before measurements and then stopping, the system continuously updates transformation parameters based on the reference sample, maintaining accurate registration throughout the entire measurement process without time loss
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 solution enables real-time image registration, eliminating the need for explicit calibration and effectively addressing thermal drift during measurements, thus improving the accuracy and reliability of multispectral imaging.
Implementation Method 1
determine a spatial correlation between the first and second images based on a spectral crosstalk between the first and second spectral channels
Implementation Method 2
a first detector element configured to capture a first image of a sample in a first spectral channel
Implementation Method 3
at least a second detector element configured to capture a second image of the sample in a second spectral channel
Data Source
AI summary
A multispectral microscope system includes a first detector element for capturing a first image of a sample in a first spectral channel, and at least a second detector element for capturing a second image of the sample in a second spectral channel. The first detector element includes a first detector array. The second detector element includes a second detector array different from the first detector array. The microscope system further includes a processor for determining a spatial correlation between the first and second images based on a spectral crosstalk between the first and second spectral channels and registering the first and second images based on the spatial correlation.