Watershed Transform for Flow Cytometry Signal Thresholding
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Solution Overview
Problem
Flow cytometry faces challenges in capturing particle events while removing noise and varying nucleated cell counts, leading to inconsistent fluorescent signals across different samples, which affects the accuracy of cellular analysis in body fluids.
Innovation Solution
The method applies a watershed transform to signals from body fluid samples stained with fluorescent dye, iteratively identifying dominant peaks and valleys to set custom thresholds for distinguishing different cell types, including nucleated and non-nucleated cells, thereby improving signal analysis and reducing noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If flow cytometry is used to identify and enumerate cell types, then cellular analysis capability is improved, but noise capture and signal consistency deteriorate
Solution Approach 1:
The patent applies watershed transform algorithm to the signal data before threshold setting to pre-process and separate the signal distribution into distinct peaks and valleys. This preliminary transformation organizes the raw signal data into a structured format that facilitates accurate threshold determination and noise rejection, resolving the contradiction between capturing cellular events and rejecting noise.
Solution Approach 2:
The patent replaces traditional fixed or manual threshold setting methods with an automated algorithmic approach using watershed transform. This substitution of mechanical/manual operations with computational processing enables dynamic adaptation to varying signal conditions, improving both noise rejection and cellular event capture consistency across different samples.
2Ease of manufacture
If traditional threshold setting is used for signal analysis, then process simplicity is maintained, but signal analysis accuracy deteriorates due to varying nucleated cell counts
Solution Approach 1:
The patent implements a self-adjusting threshold determination system where the watershed transform algorithm automatically identifies optimal thresholds based on the actual signal distribution in each sample. The system serves itself by adapting to varying nucleated cell counts and signal characteristics without requiring manual intervention or complex calibration, thus maintaining process simplicity while improving accuracy.
Solution Approach 2:
The patent dynamically changes the threshold parameter based on the signal characteristics of each sample. Instead of using a fixed threshold, the watershed transform identifies variable thresholds that adapt to the specific signal distribution, peak locations, and valley depths of each sample, thereby maintaining accuracy across different nucleated cell counts while keeping the overall process simple and automated.
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
This approach enhances the accuracy of cellular analysis by setting specific thresholds for each sample, reducing noise, and improving the distinction between cellular and non-cellular events, leading to more reliable cell type classification and count in body fluids.
Implementation Method 1
the body fluid sample is stained with a fluorescent dye, where the fluorescent dye permeates a cell membrane and binds to a nucleic acid to form a dye complex within the cell
Implementation Method 2
one or more of a variety of detectors record data based on the interaction of the cells with the applied energy
Data Source
AI summary
Methods, devices, and systems for automated cellular analysis of a body fluid sample are disclosed. The methods, devices, and systems apply watershed transform to data, generated by flowing a body fluid sample through a flow cytometer, to determine threshold(s) to be used for analysis of the data.