Microscope Z-Stack Boundary Detection Using Blurriness Extrema

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Solution Overview

Problem

Existing methods for determining the boundaries of a z-stack in microscopy are time-consuming and inefficient, especially for samples with varying focal planes, leading to incomplete image acquisition or unnecessary image capture.

Innovation Solution

A method using blurriness-W metric functions to automatically determine z-stack boundaries by identifying focal positions with primary and secondary extrema, allowing for efficient and user-friendly z-stack imaging without manual input.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual determination of z-stack boundaries is performed, then the user can observe the sample to learn the approximate extent of object depth, but it is very time consuming and requires user intervention

Engineering Contradiction:

Improveaccuracy of boundary determinationVSAvoidtime for boundary determination

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system automatically determines z-stack boundaries by analyzing images captured during autofocus operations. The processor identifies the first image with the object and the last image with the object based on autofocus metric values, eliminating the need for manual user observation and boundary setting. This self-service approach resolves the contradiction by making the system determine boundaries autonomously without time-consuming manual intervention.

Inventive Principle:

Principle #25Self-service

2Ease of operation

If fixed z-stack limits are set, then acquisition is simplified, but it may lead to empty images or z-stack not including boundaries of sample leading to missing image information

Engineering Contradiction:

Improvesimplicity of acquisition processVSAvoidcompleteness of image data

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The z-stack boundaries are determined dynamically based on the actual sample extent detected during autofocus operations. The processor analyzes each autofocus image to identify where the object appears and disappears, automatically adjusting the z-stack limits to match the sample boundaries. This dynamic approach resolves the contradiction by adapting the acquisition range to each sample rather than using fixed limits, ensuring complete image data without empty images.

Inventive Principle:

Principle #15Dynamics

3Adaptability or versatility

If manual determination of z-stack boundaries is performed for each sample region, then the boundaries can be adapted to samples with different regions and focal plane variations, but it is very time consuming

Engineering Contradiction:

Improveadaptability to different sample regionsVSAvoidacquisition speed

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system automatically adapts to different sample regions and focal plane variations by analyzing autofocus images captured during the focusing process. The processor identifies object boundaries in each image and determines z-stack limits that accommodate the specific sample geometry, eliminating the need for manual adaptation while maintaining high productivity through automated processing of the captured images.

Inventive Principle:

Principle #25Self-service

4Measurement precision

If the user observes the sample beforehand to determine boundaries, then the user can learn the approximate extent of object depth, but it requires time and user intervention before acquisition

Engineering Contradiction:

Improveaccuracy of boundary estimationVSAvoidlevel of automatic acquisition

Core Design Contradiction:

Measurement precisionVSExtent of automation

Solution Approach 1:

The system performs preliminary image capture during autofocus operations before the actual z-stack acquisition. These preliminary autofocus images are analyzed by the processor to automatically determine the z-stack boundaries, eliminating the need for separate preliminary user observation. This preliminary automated action resolves the contradiction by performing boundary determination automatically as part of the acquisition workflow rather than requiring manual user observation.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentEP4198892B1Method for determining boundaries of a z-stack of images of an object, corresponding optical instrument and computer program therefore

Publication Date: 2026.02.25 LEICA MICROSYSTEMS CMS GMBH

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AI summary

The invention relates to a method of automatically determining boundaries (110, 120) of a z-stack of images of an object (130), which z-stack of images is to be acquired by imaging the object at different focal positions by an optical instrument, the optical instrument comprising instrument optics and a focus adjusting unit for imaging the object at different focal positions through the instrument optics, said method comprising the steps of generating a set (230) of images (231) of the object (130), each image (231) being captured at a different focal position (S1); applying a blurriness-W metric function (210) to each of the images (231) of the set (230) of images (S3), the blurriness-W metric function (210) calculating a metric value for each of the images (231), different metric values being associated to a different image sharpness or blurriness of the corresponding images (231), if the blurriness-W metric function (210) with the focal position as a variable shows a primary extremum (214) and two secondary extrema (212, 216) adjoining the primary extremum (214), the z-stack boundaries (110, 120) are determined in dependence of the focal positions assigned to the two secondary extrema (212, 216) (S4).