Optical Cell Discrimination Using Prony Algorithm FOM
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Solution Overview
Problem
Current cancer detection methods are often invasive, require large sample sizes, and have high false positive rates, limiting their effectiveness in early cancer cell discrimination.
Innovation Solution
A label-free method combining optical measurements and statistical techniques, specifically using the Prony algorithm to model optical transmission characteristics and calculate a figure of merit (FOM) for distinguishing cancerous cells from normal cells based on pole coefficients and locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional invasive methods are used for cancer detection, then detection capability is improved, but patient comfort and invasiveness worsen
Solution Approach 1:
The patent replaces invasive mechanical biopsy procedures with non-invasive optical measurement systems. The system uses light transmission through cells to obtain spectral data, eliminating the need for physical tissue sampling while maintaining diagnostic capability through optical property analysis of living cells.
Solution Approach 2:
The patent introduces optical measurements as an intermediary between non-invasive observation and cancer diagnosis. By measuring optical transmission characteristics and analyzing spectral data, the system mediates between the need for accurate detection and the desire to avoid invasive procedures, using light interaction with cells as the intermediary mechanism.
2Reliability
If traditional methods with large sample sizes are used, then statistical reliability is improved, but sample consumption and complexity worsen
Solution Approach 1:
The patent changes the measurement parameters from requiring large quantities of tissue samples to using optical transmission measurements on individual or small groups of cells. By transforming the diagnostic approach to rely on spectral characteristics rather than sample volume, the system achieves reliable diagnosis with minimal sample consumption.
3Measurement precision
If conventional methods are used for cell discrimination, then detection coverage is improved, but false positive rates worsen
Solution Approach 1:
The patent applies local quality analysis by examining specific spectral features and optical properties at particular wavelengths rather than relying on overall sample characteristics. This localized measurement approach focuses on specific absorption and transmission features that are highly discriminatory between cancerous and normal cells, reducing false positives while maintaining detection sensitivity.
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 enables accurate, non-invasive discrimination of cancerous cells from normal cells with high precision, reducing false positives and improving early cancer detection capabilities.
Implementation Method 1
observing and measuring optical transmission characteristics of the plurality of cells using a spectrophotometer
Data Source
AI summary
There is provided a system and method for detection of cancerous cells from an organ tissue. The system includes a plurality of cells obtained from the organ tissue, a light source for directing light through the plurality of cells and an image sensor for detecting and measuring optical transmission characteristics of the plurality of cells. The proposed method includes modeling the measured optical transmission characteristics using a statistical algorithm and calculating a figure of merit (FOM) for each of the plurality of cells for enhancing identification accuracy of cancerous cells, wherein the FOM is calculated from pole coefficients and locations corresponding to the plurality of cells.