Automated Microscopic Cell Analysis Using Uniform Imaging Chambers
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Solution Overview
Problem
Existing methods for microscopic cell analysis, such as CBC, are time-consuming, prone to errors, require skilled operators, and are limited by the need for accurate measurement of diluent volumes and precise chamber dimensions, making them unsuitable for portable, easy-to-use analyzers.
Innovation Solution
A single-use test cartridge with a metering chamber, imaging chamber, and automated microscope that allows for precise sample collection, mixing, and analysis without requiring skilled operators, using a known dilution ratio and reproducible chamber geometry to ensure a homogeneous cell layer for accurate counting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated impedance or flow cytometry methods are used for rapid cell counting, then productivity is improved, but measurement precision deteriorates due to ambiguous impedance or scatter profiles requiring manual review
Solution Approach 1:
The patent combines automated imaging with machine learning analysis to merge the speed of automation with the precision of microscopic visualization. The system captures images of cells and uses trained neural networks to classify them, achieving both rapid processing and high accuracy by integrating multiple methodologies rather than relying on a single technique.
Solution Approach 2:
The patent replaces traditional mechanical impedance-based counting with optical imaging and computational analysis. Instead of using physical principles like electrical impedance or light scattering, the system uses digital image capture and machine learning algorithms to identify and classify cells, substituting mechanical measurement systems with information processing systems.
2Measurement precision
If manual microscopic cell counting is performed, then measurement precision is improved, but productivity deteriorates due to time-consuming manual operation
Solution Approach 1:
The patent implements self-service through automated image capture and analysis systems. The microscope automatically focuses, captures images, and the machine learning model automatically classifies cells without requiring continuous manual intervention. The system serves itself by using algorithms to perform tasks that would otherwise require skilled technicians, maintaining precision while dramatically improving throughput.
Solution Approach 2:
The patent substitutes manual human observation and classification with automated optical imaging and computational image analysis. The machine learning models replace the human visual system and cognitive classification process, enabling rapid automated analysis while preserving the accuracy benefits of microscopic examination.
3Measurement precision
If centralized laboratory analyzers are used, then measurement precision is improved, but ease of operation deteriorates due to requirement for skilled operators and centralized location
Solution Approach 1:
The patent makes the system self-sufficient by embedding automated sample preparation, imaging, and analysis capabilities in a single integrated platform. The device automatically performs focal plane detection, image capture, and cell classification without requiring skilled operators to manually adjust parameters or interpret results. The machine learning models handle complex decision-making, making the system as easy to operate as basic equipment while maintaining laboratory-grade precision.
Solution Approach 2:
The patent creates a universal platform that combines multiple functions—sample handling, automated microscopy, image processing, and cell classification—into a single system. This multi-functional device can perform various cell analysis tasks across different applications, reducing the need for specialized equipment and expert operators while maintaining high measurement precision through integrated automated processes.
4Measurement precision
If diluent volume measurement and chamber dimension precision are required, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces physical measurement systems for diluent volume and chamber dimensions with computational methods. Instead of using precision mechanical gauges or volumetric measurements, the system uses automated image analysis and machine learning models to directly estimate cell concentration from images. This substitution of mechanical measurement with information processing simplifies the hardware while maintaining or improving measurement accuracy.
Solution Approach 2:
The patent changes the measurement parameters from physical dimensions (volume, length) to optical and computational parameters (image intensity, pixel counts, machine learning features). By transforming the measurement approach from direct physical measurement to indirect computational analysis, the system eliminates the need for precise mechanical calibration while achieving accurate concentration measurements through algorithmic processing.
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
Enables rapid, accurate CBC analysis with reduced operator skill requirements, eliminating the need for precise diluent measurement and chamber dimensions, and allowing point-of-care testing with improved accuracy and reduced error rates.
Implementation Method 1
an automated microscope for analyzing cells in a biological sample
Implementation Method 2
a digital camera to capture images
Data Source
AI summary
Disclosed are single-use test cartridges, cell analyzer apparatus, and methods for automatically performing microscopic cell analysis tasks, such as counting and analyzing blood cells in biological samples. A small measured quantity of a biological sample, such as whole blood, is placed in a mixing bowl on the test cartridge after being inserted into the analyzer. The analyzer also deposits a known amount of diluent/stain in the bowl and mixes it with the blood. The analyzer takes a measured amount of the mixture and dispenses in a sample cup on the cartridge in fluid communication with an imaging chamber. The geometry of the imaging chamber is chosen to maintain the uniformity of the mixture, and prevent cells from crowding or clumping as it is transferred into the chamber by the analyzer. Images of all of the cellular components within the chamber are counted and analyzed to obtain a complete blood count.