Depth-Resolved OCT Signal Normalization for Glaucoma Diagnosis
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Solution Overview
Problem
Current depth-resolved imaging techniques, such as OCT, produce images that do not accurately reflect physical or optical properties of tissues due to complex light interactions, leading to artifacts like shading and attenuation, which complicate glaucoma diagnosis by obscuring tissue structures and introducing unreliable measurements.
Innovation Solution
The method involves analyzing measured data over a range of depths to calculate normalized physical or optical properties by modeling light interaction with tissue, iteratively determining local attenuation coefficients, and normalizing signals to account for instrument errors and ocular opacities, thereby decoupling the effects of surrounding tissue structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional OCT imaging techniques are used to capture depth-resolved backscatter signal intensity, then imaging speed and coverage are improved, but measurement precision deteriorates due to complex light interactions causing artifacts like shading and attenuation
Solution Approach 1:
The patent introduces an intermediary computational model that simulates light propagation and interaction with tissue. This model acts as a mediator between the raw OCT signals and the final tissue property measurements, correcting for attenuation and scattering effects through iterative optimization. The model includes components for incident light intensity, attenuation coefficients, and backscatter coefficients that work together to reconstruct accurate tissue properties.
Solution Approach 2:
The patent replaces direct mechanical/optical measurement with a computational approach. Instead of relying solely on the physical OCT signal intensity, the system uses iterative mathematical optimization to solve for tissue properties. This substitution of computational mechanics for direct optical measurement allows correction of artifacts while maintaining imaging speed.
2Device complexity
If raw OCT signal intensity is used directly to represent tissue properties, then device complexity is reduced, but reliability deteriorates due to dependence on incident beam strength and surrounding tissue structure
Solution Approach 1:
The patent transforms the interpretation of OCT signals by changing from direct intensity measurement to iterative optimization of tissue property parameters. The system solves for attenuation coefficients and backscatter coefficients that best reproduce the measured signal, rather than using the signal intensity directly. This parameter transformation makes measurements reliable by decoupling them from incident beam variations and surrounding tissue effects.
3Measurement precision
If normalization to reference structures is performed to correct for instrument errors and ocular opacities, then measurement precision is improved, but device complexity increases due to additional processing steps
Solution Approach 1:
The patent merges the normalization process with the iterative optimization framework. Rather than applying normalization as a separate preprocessing or postprocessing step, the reference structure information is integrated into the optimization model itself. The model simultaneously fits the measured signal and incorporates reference measurements to solve for tissue properties, combining multiple functions into a unified computational approach.
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 results in images that accurately represent tissue properties, reducing artifacts and providing reliable data for diagnosis and monitoring of glaucoma by isolating the physical or optical properties of interest, improving segmentation and disease assessment.
Implementation Method 1
The interaction of the light and the media can be complex, because interaction does not only take place at a single depth. Instead, the incident bundle generally interacts with many and/or all layers it passes through, scatters at some depth and the scattered beam again interacts with the media until it arrives at the detector.
Implementation Method 2
with OCT techniques, the sample is probed by a coherent light source and the depth-resolved backscatter signal intensity is recorded
Implementation Method 3
the resulting backscattered beam again has to pass through some part of the media before it reaches the detector and is therefore further attenuated
Data Source
AI summary
In depth-resolved imaging of scattering media, incident light interacts with tissue in a complex way before the signal reaches the detector: Light interacts with media between the light source and a specific depth, then scatters at that depth and the backscattered light again interacts with media on its way to the detector. The resulting depth-resolved signal therefore likely does not directly represent a physical or optical property of the media at those depths. Exemplary systems, methods and computer-accessible medium can determine physical or optical properties based on such depth-resolved signals. For example, almost all the light can interact with the media, and that the energy of the incident light at a certain depth is likely therefore related to the integral of the scattered light from all deeper locations. Based on the detected signals, the properties of the media can be estimated in an iterative way.