Resolution-Enhanced OCT via Coherent Averaging and Deconvolution
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Solution Overview
Problem
Optical coherence tomography (OCT) systems face limitations in enhancing image resolution without modifying the optical system, as traditional methods often require hardware changes that come with tradeoffs such as reduced field-of-view or increased noise.
Innovation Solution
The technology employs a processing platform to acquire and reconstruct multiple OCT image sets, coherently average them to suppress noise, and computationally expand the spatial bandwidth using deconvolution, allowing for resolution enhancement without altering the optical system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hardware modifications are made to enhance OCT image resolution, then image resolution is improved, but field-of-view is reduced and noise increases
Solution Approach 1:
The patent replaces hardware modifications with computational processing. Specifically, it uses coherent averaging of multiple OCT datasets and deconvolution algorithms to enhance resolution without changing the physical optical components, thereby avoiding the tradeoffs associated with hardware-based resolution enhancement
Solution Approach 2:
The patent performs preliminary coherent averaging of multiple OCT datasets before final reconstruction. By accumulating and averaging multiple datasets with proper phase registration, the system prepares enhanced signal data that can be further processed through deconvolution to achieve superior resolution without hardware changes
2Measurement precision
If hardware modifications are made to enhance OCT image resolution, then image resolution is improved, but noise increases
Solution Approach 1:
The patent substitutes hardware-based resolution enhancement with computational methods. By using coherent averaging and deconvolution algorithms, the system achieves resolution enhancement while maintaining lower noise levels compared to hardware modifications
Solution Approach 2:
The patent converts the redundancy of multiple acquired datasets into a benefit through coherent averaging. By properly phase-registering and averaging multiple datasets, the system transforms what would be redundant information into enhanced signal-to-noise ratio and improved resolution
3Object-generated harmful factors
If multiple OCT datasets are coherently averaged to suppress noise, then signal-to-noise ratio is enhanced, but processing complexity increases
Solution Approach 1:
The patent extracts and processes only the necessary phase and amplitude information from multiple OCT datasets. By focusing computational efforts on coherent averaging of the complex OCT signals and subsequent deconvolution, the system manages processing complexity while achieving effective noise suppression
4Measurement precision
If computational bandwidth expansion is performed to enhance resolution, then spatial bandwidth is expanded, but processing complexity increases
Solution Approach 1:
The patent performs preliminary coherent averaging of multiple datasets before applying deconvolution for bandwidth expansion. This preliminary noise suppression prepares the data for more effective and efficient deconvolution processing, reducing the computational burden compared to applying deconvolution directly to single datasets
Data Source
AI summary
Methods, systems, and devices for generating resolution-enhanced space-domain image of a target sample based on optical coherent tomography (OCT) imaging technologies are disclosed. In an aspect, a system includes a processing platform comprising one or more processing devices operatively coupled to one or more memory devices. The processing platform is configured to acquire a plurality of related sets of optical coherence tomography (OCT) image data for a target object volume, reconstruct space-domain OCT images for each of the plurality of sets of OCT image data, coherently average the reconstructed space-domain OCT images to suppress noise or enhance a signal-to-noise ratio, and computationally expand a spatial bandwidth of the coherent-averaged OCT image data via deconvolution.