Microtome Section Quality Assessment via Image Recognition
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Solution Overview
Problem
The production of high-quality thin sections by microtome requires specialized knowledge and is labor-intensive, leading to potential misinterpretation and variability in microscopy results due to uneven section thickness and presence of grooves, especially when processing large numbers of samples.
Innovation Solution
A method and device that utilize a camera and evaluation device to assess section quality based on predefined characteristic values, enabling objective evaluation and decision-making for accepting or rejecting sections, with the option for semi-automatic or fully automatic operation after a teach-in phase.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual assessment of section quality is performed by a user, then flexibility and adaptability to different samples are maintained, but labor intensity increases and assessment quality becomes variable due to human factors
Solution Approach 1:
The patent replaces the manual mechanical assessment process with an automated image evaluation system. A camera captures images of the sectioned sample surfaces, and an evaluation device automatically analyzes these images against predefined characteristic values to determine section quality, eliminating the need for manual visual inspection while maintaining assessment accuracy.
Solution Approach 2:
The patent creates an optical copy (image) of the sectioned sample surface and evaluates this copy rather than the physical sample itself. The camera captures the surface characteristics, and the evaluation device analyzes the image data to assess quality parameters such as thickness uniformity and groove presence, allowing repeated assessments without physical contact.
2Adaptability or versatility
If manual assessment of section quality is performed by a user, then adaptability to different laboratory standards is maintained, but assessment consistency and reproducibility deteriorate due to human variability
Solution Approach 1:
The patent establishes predefined characteristic values and tolerance ranges for section quality parameters (such as maximum permissible thickness variation and groove dimensions). The evaluation device automatically compares measured values against these predetermined parameters, ensuring consistent and objective assessment results that can be reliably reproduced across different operators and laboratories.
Solution Approach 2:
The evaluation device provides automatic feedback by comparing the captured image characteristics against the predefined quality criteria and delivering an objective pass/fail decision. This closed-loop system ensures that assessment results are consistent and reproducible, as the same sample would yield identical evaluations by the automated system regardless of which operator performs the assessment.
3Reliability
If automated image evaluation is implemented, then assessment consistency and reproducibility are improved, but device complexity increases
Solution Approach 1:
The evaluation device is designed as a multi-functional system that can assess multiple section quality characteristics (thickness uniformity, groove detection, surface quality) using a single integrated platform. The same hardware and software infrastructure evaluates different parameters by loading different characteristic value sets, reducing the need for multiple separate assessment devices.
Solution Approach 2:
The patent introduces an intermediary evaluation device that acts as a mediator between the microtome sectioning process and the final quality assessment. This intermediate system captures images and performs preliminary evaluations, separating the complex evaluation function from the sectioning process and allowing for modular, manageable system architecture.
4Manufacturing precision
If strict quality criteria are enforced, then section quality and microscopy reliability are improved, but the number of rejected sections increases
Solution Approach 1:
The automated image evaluation system provides objective, quantitative assessment of section quality based on captured images. By replacing subjective manual judgment with automated analysis of characteristic values (thickness variation, groove detection), the system consistently enforces strict quality criteria without the variability inherent in manual assessment, ensuring high section quality while providing transparent rejection decisions.
Data Source
AI summary
A method and a device for producing thin sections of a sample by means of a microtome is described, in which a camera acquires at least one image of a surface generated by sectioning of the sample. With the aid of an evaluation device, the image of the surface is evaluated in terms of predefined characteristic values of a section quality. As a function of the characteristic values that are identified, a decision is then made as to whether the section of the sample is accepted or not.