Cell Grouping Detection With Ellipse Fitting for Accurate Counting
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Solution Overview
Problem
Existing cell counting systems struggle to accurately identify and quantify groupings of cells based on spatial proximity and viability, which affects the analysis of cell growth and treatment effectiveness.
Innovation Solution
An imaging system that applies filters to an image of cells, identifies groupings using connected component analysis, and fits ellipses around these groupings to determine cell membrane touch points, providing cell aggregate data for further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional cell counting methods are used, then the counting process is simple, but the accuracy of identifying cell groupings is poor
Solution Approach 1:
The patent segments the cell identification process into multiple processing stages: initial cell detection, grouping identification through connected component analysis, and individual cell characterization within groups. This segmentation allows the system to accurately identify cell groupings while managing computational complexity through staged processing.
Solution Approach 2:
The patent transitions from traditional two-dimensional image analysis to three-dimensional cell grouping analysis by incorporating spatial relationships and connectivity information. This dimensional enhancement enables accurate identification of cell clusters and their structural characteristics beyond simple planar detection.
2Measurement precision
If detailed image processing is applied to identify cell groupings, then the measurement accuracy improves, but the processing time increases
Solution Approach 1:
The patent applies preliminary filtering and preprocessing steps to identify potential cell locations and groupings before performing detailed analysis. By pre-processing the image to highlight cell boundaries and connectivity, the system reduces the computational burden of subsequent detailed processing while maintaining high accuracy in viability counting.
3Measurement precision
If cell membranes touch points are identified to distinguish single cells from groupings, then the cell counting accuracy improves, but the difficulty of detection increases
Solution Approach 1:
The patent introduces an intermediary processing layer that detects cell membrane touch points and connectivity features. This intermediary analysis of boundary interactions and spatial relationships serves as a mediator between raw image data and final cell grouping classification, making the detection of touch points more manageable and accurate.
Data Source
AI summary
Systems and methods for identifying clumps (or groupings) of cells in cell counting systems. One example method executed by an electronic processing device for an image processing system includes receiving an image, captured by an imaging device, of a sample having a plurality of cells. The image includes labeling data for each of the plurality of cells. The method includes applying filters, determined based on the labeling data, to the image, processing the image to identify a plurality of groupings of the plurality of cells, and fitting an ellipse around each of the groupings by determining ellipse data for each of the ellipses. Each respective grouping of the plurality of groupings includes at least two cells having a same viability whose cell membranes are touching at least one other cell in the respective grouping.