Cell Viability Detection Using Image Contrast and Histogram Fitting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing automated systems for analyzing cell viability in samples require the use of dyes, labels, or other compounds, necessitating specialized and often expensive equipment, and can be computationally expensive and require large training datasets.
Innovation Solution
The system receives microscope images of cells, improves contrast, performs exponential histogram fitting for auto-thresholding, applies filters, identifies cells through connected component analysis, and provides an output image indicating cell locations, thereby eliminating the need for additional compounds and equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dyes, labels, or other compounds are used to determine cell viability, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts and eliminates the need for dyes, labels, and specialized equipment by using inherent cell properties (refractive index, membrane potential) that can be detected with standard microscope imaging systems. This removes the complex auxiliary substances and equipment while maintaining measurement capability.
Solution Approach 2:
The system uses the cells themselves as the measurement target without requiring external dyes or labels. The cells' inherent physical and electrical properties are exploited for detection, allowing the cells to essentially measure themselves through standard imaging techniques.
2Measurement precision
If manual cell viability counting is performed, then measurement precision is maintained, but loss of time increases
Solution Approach 1:
The patent replaces manual mechanical counting with automated image processing algorithms. The system captures images and automatically identifies and counts viable cells based on their optical properties, eliminating the need for manual inspection while maintaining accuracy.
Solution Approach 2:
The system transforms the counting process from manual observation to automated parameter analysis. By converting cell viability into detectable optical parameters (contrast, brightness) and using algorithmic processing, the system achieves both speed and precision in cell counting.
3Productivity
If existing automated systems are used, then productivity is improved, but device complexity and cost increase
Solution Approach 1:
The patent makes the system universal by using standard microscope imaging capabilities that can detect cell viability without requiring specialized equipment. The same imaging system used for general microscopy can perform viability analysis through algorithmic processing of inherent cell properties.
Solution Approach 2:
The system replaces expensive, specialized equipment with inexpensive, standard imaging components. By using readily available microscope cameras and processors instead of costly specialized devices, the system maintains productivity while reducing equipment complexity and cost.
Data Source
AI summary
Examples described herein provide systems and methods for quantifying cells. An example method includes receiving at least one image, improving a contrast of the at least one image to generate a contrast image, and performing a fit operation on the contrast image to generate a processed image. The method includes applying a filter to the processed image to generate a filtered image, identifying cells within the filtered image, and providing an output image including an indication of the cells.