OCT Angiography Artifact Reduction via Inverse Problem Estimation
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Solution Overview
Problem
Optical coherence tomography angiography (OCTA) is limited by long acquisition times and motion artifacts, as well as projection or decorrelation tail artifacts that interfere with the interpretation of retinal angiographic results due to light scattering from blood vessels, leading to inaccurate representation of vasculature in deeper retinal layers.
Innovation Solution
A mathematically sound inverse problem estimation framework is employed to reduce artifacts in OCT angiography images by calculating motion contrast information and using multiplicative or additive mixing models to generate images with reduced artifacts, allowing for controlled artifact removal and improved visualization of vasculature.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high density of sampling points is used to achieve high resolution en face visualization, then image resolution is improved, but acquisition time increases by up to an order of magnitude
Solution Approach 1:
The patent segments the OCT data processing into two distinct components: structural information (amplitude) and motion information (phase or complex). By separating these components, the system can process motion contrast using only the phase or complex data without requiring high-density sampling for structural detail, thereby reducing acquisition time while maintaining angiography quality
Solution Approach 2:
The patent extracts motion contrast information specifically from the phase or complex portion of OCT data, isolating the angiography signal from the structural amplitude information. This extraction allows the system to achieve angiographic imaging with lower sampling density since motion contrast does not require the same spatial resolution as structural imaging
2Reliability
If longer acquisition times are used to reduce motion artifacts, then image quality is improved, but patient comfort and clinical efficiency deteriorate
Solution Approach 1:
The patent applies motion correction algorithms to register and correct for eye movements before the angiography processing is completed. By performing preliminary motion correction on the acquired data, the system can use shorter acquisition times while still achieving high-quality artifact-free images, thereby improving patient comfort without sacrificing image quality
Solution Approach 2:
The system uses phase information as a feedback mechanism to detect and correct motion artifacts in real-time during data acquisition. This feedback approach allows for shorter scan times because the system can actively compensate for motion rather than requiring excessively long acquisition times to average out motion effects
3Productivity
If projection artifacts are not corrected, then processing speed is maintained, but accuracy of vasculature interpretation in deeper layers deteriorates
Solution Approach 1:
The patent extracts and removes the projection artifact component from the angiography signal by using amplitude attenuation maps to identify and eliminate signals originating from superficial vessels that project into deeper layers. This extraction process maintains processing efficiency while significantly improving the accuracy of vasculature interpretation in deeper retinal layers
Solution Approach 2:
The patent introduces amplitude attenuation maps as an intermediary tool to mediate between the raw angiography signal and the final processed image. These maps serve as a correction layer that removes projection artifacts without requiring complex reprocessing of the original data, thereby maintaining processing speed while improving interpretation accuracy
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 effectively minimizes artifacts in OCT angiography images, reducing acquisition time and improving the accuracy of vasculature visualization by isolating and correcting for motion and decorrelation tail artifacts, thereby enhancing the interpretation of retinal angiograms.
Implementation Method 1
Optical coherence tomography (OCT) is a noninvasive, noncontact imaging modality that uses coherence gating to obtain high-resolution cross-sectional images of tissue microstructure
Implementation Method 2
the interferometric signal between light from a reference and the back-scattered light from a sample point is recorded
Implementation Method 3
After a wavelength calibration, a one-dimensional Fourier transform is taken to obtain the scattering profile of a sample along the OCT beam
Implementation Method 4
The key point of OCT angiography processing methods is to extract localized signal variations from the bulk motion signal of a background tissue by comparing OCT signals, such as B-scans, captured at different closely-spaced time points
Implementation Method 5
projection or decorrelation tail artifacts that interfere with the interpretation of retinal angiographic results due to light scattering from blood vessels
Data Source
AI summary
Various methods for reducing artifacts in OCT images of an eye are described. In one exemplary method, three dimensional OCT image data of the eye is collected. Motion contrast information is calculated in the OCT image data. A first image and a second image are created from the motion contrast information. The first and the second images depict vasculature information regarding one or more upper portions and one or more deeper portions, respectively. The second image contains artifacts. Using an inverse calculation, a third image is determined that can be mixed with the first image to generate the second image. The third image depicts vasculature regarding the same one or more deeper portions as the second image but has reduced artifacts. A depth dependent correction method is also described that can be used in combination with the inverse problem based method to further reduce artifacts in OCT angiography images.