Optoretinography Processing with Phase-Derived OCT Velocity Profiles
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Solution Overview
Problem
Existing optical coherence tomography (OCT) systems face challenges in accurately identifying retinal layer boundaries, particularly in cases with poor axial resolution or noisy data, which hinders effective optoretinography (ORG) analysis.
Innovation Solution
A computer-implemented method processes phase components of OCT images to calculate a velocity profile, compensating for bulk motion, and uses algorithms like PCA to determine retinal layer boundaries based on velocity variations, enabling reliable identification of layer positions without relying on intensity peak detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If intensity peak detection is used to identify retinal layer boundaries, then the method is simple to implement, but it fails in cases with poor axial resolution or noisy data
Solution Approach 1:
The patent transforms the boundary identification approach from intensity-based parameters to velocity-based parameters. By calculating velocity profiles from phase components of OCT images and identifying boundaries at velocity extrema (maxima or minima), the method achieves reliable boundary detection in cases with poor axial resolution or noisy data where intensity peak detection fails.
2Measurement precision
If velocity profile calculation is used to identify retinal layer boundaries, then boundary identification accuracy is improved in noisy data, but computational complexity increases
Solution Approach 1:
The patent performs preliminary processing of the OCT data by calculating velocity profiles from phase components before boundary identification. This preliminary velocity calculation enables subsequent boundary detection at velocity extrema, improving accuracy while managing computational complexity through a structured two-stage approach.
3Measurement precision
If adaptive optics or tracking systems are used to improve ORG analysis, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces mechanical/optical compensation systems (adaptive optics and tracking systems) with a computational approach. By using velocity profile analysis of phase components from standard FD-OCT systems, the method achieves effective ORG analysis without requiring additional complex hardware, thereby reducing system complexity and cost while maintaining 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
This approach allows for effective layer segmentation and ORG response extraction from FD-OCT systems with poor axial resolution, facilitating ORG analysis in various retinal regions, including those with weak signal intensities, without the need for adaptive optics or tracking systems.
Implementation Method 1
a spectral interferogram resulting from an interference between light in the reference arm and light in the sample arm of the interferometer
Implementation Method 2
Optical coherence tomography (OCT) is an imaging technique based on low-coherence interferometry
Implementation Method 3
phase-resolved OCT imaging systems are able to resolve displacements smaller than 10 nm, which may be much smaller than the axial resolution of the system or the wavelength of the light used in imaging
Data Source
AI summary
A computer-implemented method of processing respective phase components of a first OCT image and a second OCT image of a sequence of OCT images of a common portion of a retina acquired by a Fourier-domain OCT imaging system after stimulation of the common portion by an optical stimulus, the common portion comprising a layer of the retina whose thickness changed during acquisition of the sequence of OCT images, to determine an indication of a position along an axial direction in the OCT images of a boundary of the layer, the method comprising: processing the phase component of the first OCT image and the phase component of the second OCT image to calculate a velocity profile indicative of a distribution, along the axial direction, of velocity within the common portion of the retina; and determining the indication based on the calculated velocity profile.