Light Reflection Imaging for Turbid Tissue Optical Parameters
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Solution Overview
Problem
Current methods face challenges in accurately quantifying optical parameters and microstructures of tissues, particularly at short light source-detector distances, due to limitations in reflectance empirical models and the difficulty in analyzing phase functions from reflectance measurements.
Innovation Solution
The method combines small-angle approximation (SAA) of radiative transfer to establish a quantitative analysis relation between near-distance sub-diffuse scattering light reflectance and the scattering medium phase function, using low- and high-frequency reflectance formulas to obtain optical parameters and microstructural characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If diffusion approximation is used for radiative transfer analysis, then the analysis is simplified and computationally easier, but it cannot work accurately at short light source-detector distances
Solution Approach 1:
The patent changes the parameter of light propagation distance by separating the analysis into two distinct distance regimes: short distances (0 < ρ < 3lt) using small-angle approximation and large distances (ρ ≥ 3lt) using diffusion approximation. This parameter-based segmentation allows each model to operate in its optimal accuracy range, resolving the contradiction between computational simplicity and measurement accuracy.
Solution Approach 2:
The patent segments the radiative transfer analysis into two distinct spatial frequency domains: low-frequency component (Isnake+Idiffuse) for large source-detector distances where diffusion approximation is valid, and high-frequency component (ISAA) for short distances where small-angle approximation is required. This segmentation enables each method to be applied where it is most accurate, eliminating the limitation of using a single model across all distances.
2Ease of operation
If empirical reflectance models are used for short light source-detector distances, then some analysis capability is provided, but they have respective limitations and cannot accurately quantify phase function
Solution Approach 1:
The patent creates a composite reflectance model that combines two different theoretical approaches: the small-angle approximation model (ISAA) and the diffusion approximation model (Isnake+Idiffuse). By compositeing these two models with their respective validity ranges, the patent achieves comprehensive accuracy across all source-detector distances while maintaining the ability to quantify phase function parameters, overcoming the limitations of individual empirical models.
3Device complexity
If a single analysis model is used for all light source-detector distances, then the model is simpler to implement, but it cannot accurately analyze both short and large distance reflectance
Solution Approach 1:
The patent introduces a dynamic selection mechanism that automatically chooses the appropriate analysis model based on the source-detector distance parameter. The system dynamically switches between small-angle approximation (for ρ < 3lt) and diffusion approximation (for ρ ≥ 3lt), enabling a single unified framework to adaptively handle both short and large distance scenarios with high accuracy without requiring complex manual model selection.
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 determination of optical parameters and microstructures, improving the analysis of turbid media's optical properties and phase functions, especially in biomedical optics and remote sensing, by providing a comprehensive model for rapid quantification.
Implementation Method 1
Elastic scattering of light has long been used for analyzing random media. Reflectance spectroscopy and imaging are widely used noninvasive methods for measuring the optical properties of random media
Implementation Method 2
Since radiative transfer (RT) describes the propagation of light in random media, the reflectance of scattered light is essentially a difficult problem
Implementation Method 3
the diffusion approximation usually adopted for the RT cannot work
Data Source
AI summary
A light reflection imaging method for acquiring optical parameters and microstructures of tissues in a large area, comprising a turbid medium reflectance calculation method applicable at a random spatial distance and in an entire spatial frequency domain, and a method of measuring the reflectance of a turbid medium at high and low spatial frequencies and inverting the obtained light reflectance to obtain optical parameters of the medium. The inversion method may be a table lookup method or a formula fitting method. The measurement of sub-diffuse and diffuse light reflectance of the turbid medium can be used for measuring the optical properties of the turbid medium and microstructures including a phase function and the like in a large area.