Polarization-sensitive OCT Jones Matrix Eigenvalue Decomposition
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Solution Overview
Problem
Existing polarization-sensitive optical coherence tomography (PS-OCT) methods require extensive data storage and processing time, making them impractical for diagnostic equipment with limited processing power, especially when estimating phase retardation and birefringence properties.
Innovation Solution
A novel method utilizing density functions from quantum mechanics to analogize the probability of wave functions to the Jones matrix, allowing for the rapid estimation of polarization characteristics, including phase retardation, by vectorizing the Jones matrix and performing eigenvalue decomposition on a 4x4 coherence or covariance matrix, and calculating pseudo probabilities to estimate phase retardation, diattenuation, and birefringence axes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sets of phase difference distribution for different ESNRs are created and stored using Monte Carlo simulation, then the true phase value can be estimated accurately, but the processing time becomes excessively long and data storage requirements become enormous
Solution Approach 1:
The patent pre-calculates and stores lookup tables containing phase difference distribution characteristics for various ESNR values before actual OCT measurement. This preliminary preparation allows the system to quickly retrieve pre-computed statistical characteristics during measurement without performing time-consuming Monte Carlo simulations in real-time, thus resolving the contradiction between accurate phase estimation and processing time
Solution Approach 2:
Instead of storing enormous amounts of raw Monte Carlo simulation data for every possible scenario, the patent creates simplified lookup tables that capture the essential statistical characteristics. These compact representations serve as copies that retain the necessary information for accurate phase estimation while occupying minimal storage space and enabling rapid access during measurement
2Measurement precision
If enormous data sets are referenced at each pixel of OCT data, then accurate phase estimation is achieved, but the processing power requirements exceed what diagnostic equipment can provide
Solution Approach 1:
The patent extracts only the essential statistical characteristics from the full Monte Carlo simulation data, creating compact lookup tables that contain only the necessary information for phase estimation. This extraction process removes unnecessary computational complexity while retaining the core functionality needed for accurate measurement
Solution Approach 2:
The patent transforms the complex multi-dimensional phase difference distribution problem into a simplified lookup table structure indexed by ESNR values. By changing the representation parameters from raw simulation data to pre-computed statistical moments and distribution characteristics, the system achieves accurate phase estimation with minimal processing power
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 fast and accurate quantitative analysis of birefringence properties, significantly reducing processing time and making it feasible for diagnostic equipment with limited processing power.
Implementation Method 1
a wavelength sweeping light source (101) which allows sweeping with a temporally changing wavelength
Implementation Method 2
a polarization beam splitter (106) provided in the polarization-dependent delay line (133), to be split into two beams in different polarization states
Implementation Method 3
Birefringence which changes a polarization state occurs in tissues in which molecules are arranged in a same direction
Implementation Method 4
a photodetector (230) that detects the intensity of the light (201)
Data Source
AI summary
The optical coherence tomography includes a processor, wherein the processor is configured to: vectorize the Jones matrix and then convert the vectorized Jones matrix into an expanded matrix; calculate at least an eigenvalue and at least an eigenvector of the expanded matrix by performing an eigenvalue decomposition to the expanded matrix; and estimate the polarization characteristic of the subject by using at least an eigenvalue and at least an eigenvector of the Jones matrix acquired based on the at least eigenvalue and the at least eigenvector of the expanded matrix.