Automated Optical Training System for Microscopy Sample Evaluation
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Solution Overview
Problem
Existing evaluation methods for samples in microscopy are often developed specifically for each application and sample type, leading to inefficiencies and reduced flexibility, with a need for improved development and provision of evaluation methods that are specific to the application system and sample type.
Innovation Solution
A method involving an optical training system to develop and provide evaluation methods by automated training, where training information defines the evaluation method, allowing for distribution based on sample and application technology, enabling flexible use across multiple sample types and technologies, and potentially simplifying the application system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If evaluation methods are developed specifically for each application and sample type, then the reliability and accuracy of evaluation is improved, but the device complexity and development time increase
Solution Approach 1:
The patent uses optical training systems to create virtual training data that copies real sample characteristics without requiring physical samples. This allows evaluation methods to be trained and validated digitally, reducing the complexity of developing specific evaluation methods for each sample type while maintaining reliability through accurate optical modeling
Solution Approach 2:
The patent develops a universal optical training system that can generate training data for multiple sample types and application technologies. This multi-functional system eliminates the need to develop separate evaluation methods for each specific case, reducing development complexity while maintaining evaluation reliability across different applications
2Measurement precision
If elaborate evaluation methods are developed for specific sample types, then the measurement precision is improved, but the loss of time in development and provision increases
Solution Approach 1:
The patent performs preliminary training of evaluation methods using optical training systems to generate virtual training data before actual sample evaluation. This preliminary action allows evaluation methods to be pre-optimized for specific sample types and application technologies, reducing the time required for development and provision while maintaining measurement precision
Solution Approach 2:
The optical training system enables automated generation of training data and self-training of evaluation methods without extensive manual intervention. This self-service capability significantly reduces development time while maintaining the precision needed for specific sample type evaluation
3Productivity
If automated training is used for development, then the productivity is improved, but the device complexity increases
Solution Approach 1:
The patent replaces manual evaluation method development with automated optical training systems that use virtual training data. This substitution of mechanical/manual processes with automated optical and computational systems dramatically improves development productivity, with the added complexity offset by the elimination of manual development activities
Data Source
AI summary
The invention relates to a method for providing at least one evaluation method for samples (2) in at least one optical application system (5) of a microscope-based application technology,where the following steps are performed:developing the evaluation method at least by an automated training (130) of an evaluation means (60) for an evaluation (120) of a specific type of sample on the basis of the application technology by an optical training system (4), the training (130) determining a training information (200) which at least partially defines the evaluation method,at least the training information (200) for distributing (140) the evaluation method to the at least one application system (5), wherein the provision takes place as a function of the type of sample and of the application technology.