Sample-Aware Microscope Correction Ring Control for Aberration Reduction
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Solution Overview
Problem
The challenge of optimally setting the objective correction ring in microscopes, particularly for high-resolution applications and living cell microscopy, is complicated by varying conditions such as cover glass thickness, sample temperature, and refractive index differences, leading to image aberrations and requiring manual adjustments that can disrupt focus.
Innovation Solution
A method using a machine learning or machine-learned algorithm to determine an optimal setting for the objective correction ring based on raw images, incorporating sample information and iteratively adjusting the ring to minimize aberrations, either manually or automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of the objective correction ring is used, then the user can set the correction ring, but the process is time-consuming and requires repeated manual adjustments to compensate for focus offset changes
Solution Approach 1:
The patent replaces manual mechanical adjustment of the correction ring with an automated motor-driven system controlled by a microprocessor. The microprocessor receives image quality data, processes it through evaluation algorithms, and automatically adjusts the motor-driven correction ring to optimize imaging parameters, eliminating the need for repeated manual adjustments and focus compensation.
Solution Approach 2:
The patent implements a feedback control system where the microprocessor continuously monitors image quality parameters, compares them against predetermined criteria, and automatically adjusts the correction ring setting accordingly. This closed-loop feedback mechanism enables the system to self-optimize the correction ring position based on actual image quality without requiring manual intervention.
2Manufacturing precision
If the objective correction ring is adjusted to correct imaging aberrations, then image quality improves, but the focus offset in the sample changes requiring readjustment
Solution Approach 1:
The patent employs feedback control to automatically compensate for focus offset changes. The microprocessor monitors image quality parameters and dynamically adjusts both the correction ring and focus position to maintain optimal imaging conditions, ensuring that aberration correction does not result in unacceptable focus degradation.
Solution Approach 2:
The patent makes the correction ring adjustment dynamic and adaptive rather than static. The system continuously adjusts the correction ring position and focus offset based on real-time image quality evaluation, allowing the microscope to adapt to varying sample conditions and maintain optimal performance without requiring manual readjustment.
3Measurement precision
If high-resolution objectives are used, then resolution increases, but the optical system becomes increasingly sensitive to deviations from design conditions
Solution Approach 1:
The patent dynamically changes the optical parameters of the correction ring based on actual imaging conditions. The microprocessor adjusts the correction ring position and other optical parameters in real-time to compensate for deviations from design conditions such as varying cover glass thickness, sample temperature, and refractive index differences, thereby maintaining high resolution across diverse conditions.
Solution Approach 2:
The patent implements feedback control to continuously monitor and compensate for optical system sensitivity to condition deviations. The microprocessor evaluates image quality parameters and automatically adjusts the correction ring and other optical settings to maintain optimal performance, reducing the impact of sensitivity to environmental and sample variations.
Data Source
AI summary
A method for preparing a microscope for imaging a sample. The method includes the following steps: providing the microscope for imaging the sample, wherein the microscope comprises an objective having a motor-adjustable objective correction ring for correcting imaging aberrations; acquiring sample information comprising at least one of the following indications: thickness of a cover glass, material of the cover glass, sample temperature, sample type, sample location on a sample carrier, embedding medium of the sample, or immersion medium; imaging the sample using the microscope for generating at least one raw image of the sample with a first setting of the objective correction ring; and inputting the at least one raw image and the sample information into a machine algorithm and determining a second setting of the objective correction ring, which reduces the imaging aberrations vis à vis the first setting, by means of the algorithm on the basis of the raw image and the sample information.