Adaptive Optics Reflection Microscopy With Fluorescent Distortion Sensing
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Solution Overview
Problem
Existing optical microscopy methods struggle with aberrations and scattering in biological samples, particularly in reflected-light imaging, where aberrations in the excitation and detection paths are different and difficult to separate, and conventional machine learning approaches require large data sets to correct distortions effectively.
Innovation Solution
A method using a physical light propagation model in combination with a fluorescence-capable body to determine distortion parameters efficiently, eliminating the need for extensive training data by leveraging known properties of the fluorescence body, and an irradiation apparatus with optical modulators to correct distortions in both transmission and reflection paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional machine learning approaches are used to correct distortions in reflection microscopy, then distortion correction can be achieved, but large data sets are required which consume considerable material and time resources
Solution Approach 1:
The patent introduces a fluorescent body as an intermediary object within the scattering sample. This fluorescent body serves as a known reference that emits light at a different wavelength than the excitation light, allowing the system to measure and characterize distortions without requiring complex training data sets. The fluorescent body acts as a mediator between the excitation path and detection path, enabling direct measurement of distortion parameters.
Solution Approach 2:
The patent creates a simplified model of the distortion problem by using a fluorescent body with known properties. Instead of training on large data sets of complex samples, the system copies the essential distortion characteristics through a controlled fluorescent reference object. This allows the neural network to learn distortion correction from a small, controlled data set rather than requiring extensive training data.
2Reliability
If large data sets are used to train neural networks for distortion correction, then comprehensive distortion coverage can be achieved, but material and time resources are consumed
Solution Approach 1:
The fluorescent body serves as an intermediary reference object that enables reliable distortion measurement without requiring large volumes of training data. By using this known reference with specific fluorescent properties, the system can accurately characterize distortions through direct measurement rather than statistical learning from extensive data sets.
Solution Approach 2:
The patent changes the wavelength parameter of light by using fluorescence emission at a different wavelength than excitation. This parameter change allows the system to measure distortions in a controlled manner using a small data set, as the fluorescent body's known emission characteristics provide a reliable reference for distortion characterization without requiring extensive training data.
3Measurement precision
If aberrations in excitation and detection paths are treated separately, then path-specific corrections can be made, but the complexity of separating and correcting both paths increases
Solution Approach 1:
The patent merges the measurement of excitation and detection path aberrations into a single process by using a fluorescent body that responds to excitation light. The fluorescent emission captures the combined effect of both paths' distortions in one measurement, avoiding the need for separate, complex measurement and correction procedures for each optical path.
Solution Approach 2:
The fluorescent body acts as an intermediary that naturally couples the excitation and detection paths. By placing the fluorescent body in the sample and measuring its emission, the system automatically accounts for distortions in both the excitation path (delivering light to the fluorescent body) and the detection path (collecting emitted light), simplifying the overall correction process.
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 method allows for accurate and efficient correction of distortions in optical systems, enabling high-resolution imaging through scattering bodies by using a smaller data set and known properties of fluorescence bodies, reducing computational resources and improving image clarity.
Implementation Method 1
The reflection-light distribution is at least partially reflected as fluorescence radiation by a fluorescence-capable body within the scattering body
Implementation Method 2
passing the input light distribution through a scattering body, wherein the scattering body is placed in the excitation path of the optical system so that the input-light distribution is changed to a reflection-light distribution
Data Source
AI summary
A method for optimizing parameters of a physical light propagation model. The method includes making available a physical model of a light propagation in an optical system, radiating an input-light distribution into an excitation path of the optical system using an illumination unit, passing the input light distribution through a scattering body, wherein the scattering body is placed in the excitation path of the optical system so that the input-light distribution is changed to a reflection-light distribution, recording the reflection-light distribution, transferring the recorded reflection-light distribution to the physical model, and calculating distortion parameters of the physical model based on the reflection-light distribution. The distortion parameters characterize the scattering body. The reflection-light distribution is at least partially reflected as fluorescence radiation by a fluorescence-capable body within the scattering body.