Structured-light imaging for sub-diffuse scattering parameter quantification
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Solution Overview
Problem
Current methods for measuring sub-diffuse scattering parameters in biological tissue are limited by their inability to quickly assess large areas, requiring time-intensive mechanical scanning and being insensitive to local tissue microstructure changes, while existing spatial frequency domain imaging techniques are restricted by assumptions that limit the sampling of photons experiencing few scattering events.
Innovation Solution
A structured-light imaging system that illuminates tissue with periodic spatial structure and captures remission images to determine sub-diffuse scattering parameters, using demodulation and modeling to quantify the reduced scattering coefficient and backscatter likelihood, allowing for fast, wide-field imaging without mechanical scanning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mechanical scanning of fiber optic is used to achieve localized scatter measurements, then measurement precision is improved, but productivity deteriorates due to time-intensive scanning process
Solution Approach 1:
The patent replaces the mechanical fiber optic scanning system with a stationary camera and structured light illumination system. The mechanical movement of the fiber optic probe is substituted by projecting structured light patterns (e.g., sinusoidal fringes) onto the tissue and capturing the remitted light with a stationary camera, thereby eliminating the time-intensive mechanical scanning process while maintaining measurement capability.
Solution Approach 2:
The patent transitions from point-by-point mechanical scanning in one dimension to wide-field optical imaging in two dimensions. By using structured light projection and camera capture, the system obtains spatially-resolved scatter measurements across the entire field of view simultaneously, adding a spatial dimension to the measurement process and dramatically improving productivity.
2Device complexity
If diffusion approximation is used to model light transport, then device complexity is reduced, but measurement precision deteriorates for sub-diffuse photons
Solution Approach 1:
The patent applies different modeling approaches to different spatial frequency components of the measured signal. Low spatial frequency components (diffuse regime) are analyzed using the simpler diffusion approximation, while high spatial frequency components (sub-diffuse regime) are analyzed using more sophisticated radiative transfer models or Monte Carlo simulations. This local differentiation allows the system to maintain measurement precision for sub-diffuse photons while managing overall device complexity.
Solution Approach 2:
The patent changes the modeling parameters and assumptions based on the spatial frequency of the measured signal. For sub-diffuse components, the system uses parameters that account for photon directionality and individual scattering events, rather than the lumped reduced scattering coefficient used in diffusion theory. This parameter adaptation enables accurate characterization of sub-diffuse scattering while maintaining computational feasibility.
3Productivity
If spatial frequency domain imaging is used to achieve wide-field imaging, then productivity is improved, but measurement precision deteriorates due to assumptions limiting sub-diffuse photon sampling
Solution Approach 1:
The patent dynamically adjusts the spatial frequency content of the projected structured light patterns to optimize sampling of sub-diffuse photons. By using higher spatial frequency patterns and analyzing the corresponding high spatial frequency components of the remitted light, the system enhances sensitivity to sub-diffuse scattering events while maintaining wide-field imaging capability. This dynamic optimization allows simultaneous achievement of productivity and measurement precision.
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
Enables rapid, quantitative assessment of sub-diffuse scattering parameters over large areas, providing sensitive measurements of tissue microstructure changes and improving the accuracy of tissue differentiation, particularly in clinical settings like surgery.
Implementation Method 1
Light scattering in biological tissue is a complex process that occurs as photons traverse index of refraction mismatches along their propagation path
Implementation Method 2
a camera for capturing images of the remission of the structured light by the material
Data Source
AI summary
A method for determining sub-diffuse scattering parameters of a material includes illuminating the material with structured light and imaging remission by the material of the structured light. The method further includes determining, from captured remission images, sub-diffuse scattering parameters of the material. A structured-light imaging system for determining sub-diffuse scattering parameters of a material includes a structured-light illuminator, for illuminating the material with structured light of periodic spatial structure, and a camera for capturing images of the remission of the structured light by the material. The structured-light imaging system further includes an analysis module for processing the images to quantitatively determine the sub-diffuse scattering parameters. A software product includes machine-readable instructions for analyzing images of remission of structured light by a material to determine sub-diffuse scattering parameters of the material.