Fourier-Based OCT Axial Motion Correction for Retinal Imaging
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Solution Overview
Problem
Optical coherence tomography (OCT) scans of the eye are compromised by axial motion, leading to jagged and broken images and complicating automated data analysis, particularly in retinal multilayer segmentation, due to factors like patient movement, internal body operations, and mechanical vibrations.
Innovation Solution
A method and system for axial motion correction in OCT data using Fourier transform-based periodic pattern removal and orthogonal scan correlation to estimate and correct axial motion, employing multiple pairs of orthogonal scans and Fourier domain analysis without requiring additional registration scans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If orthogonal retrace scans are used for axial motion correction, then axial motion correction is effective, but axial bulk motion and low image contrast occur when retrace scans cross the ONH or large vessels
Solution Approach 1:
The patent introduces an intermediary signal processing approach by using Fourier transform to analyze periodic patterns in the OCT data. Instead of directly using orthogonal retrace scans that cause contrast loss, the method extracts motion information through frequency domain analysis of the primary scan data, using the Fourier transform as an intermediary to separate motion artifacts from actual tissue structures.
Solution Approach 2:
The patent replaces the mechanical scanning approach (orthogonal retrace scans) with a computational signal processing method. Instead of physically scanning in orthogonal directions to correct motion, the invention uses Fourier transform-based algorithms to detect and correct axial motion artifacts computationally, substituting mechanical correction with mathematical processing.
2Measurement precision
If additional registration scans are used for motion correction, then motion correction accuracy is improved, but scan time and system complexity increase
Solution Approach 1:
The patent enables the OCT system to self-correct axial motion artifacts using only the primary volume scan data without requiring additional registration scans. The Fourier transform method extracts periodic motion patterns directly from the acquired OCT data, allowing the system to perform motion correction using its own existing data rather than needing external reference scans.
Solution Approach 2:
The patent makes the primary OCT scan data serve multiple functions: both for obtaining the diagnostic image and for motion correction. The same volume scan data is used for both imaging purposes and for extracting motion information through Fourier analysis, eliminating the need for separate registration scans and improving overall system efficiency.
3Object-generated harmful factors
If Fourier transform-based periodic pattern removal is applied, then periodic motion artifacts are removed, but non-periodic motion components may be affected
Solution Approach 1:
The patent segments the motion correction process into two distinct components: periodic motion removal using Fourier transform and non-periodic motion correction using correlation-based methods. By dividing the motion artifacts into periodic and non-periodic components, the method can apply specialized techniques for each type, removing periodic artifacts through frequency domain filtering while preserving non-periodic motion information through spatial correlation analysis.
Solution Approach 2:
The patent employs dynamic adaptive processing by combining multiple motion correction techniques that can adapt to different motion characteristics. The system dynamically selects and applies appropriate correction methods based on the detected motion patterns, using Fourier transform for periodic components and correlation-based registration for non-periodic components, making the overall correction process adaptable to varying motion conditions.
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
Improves image quality and reduces failure rates in automated retinal layer segmentation, enhancing the accuracy of retinal thickness mapping and vascular structure analysis in OCT scans.
Implementation Method 1
determining a model of a Fourier transform applicable to a segment of the first retinal layer; and removing one or more transform frequencies associated with the OCT data using the model of the Fourier transform
Data Source
AI summary
A method and system for correcting axial motion in optical coherence tomography (OCT) data is provided. The method includes collecting, by a processor disposed of in an OCT device, a volume scan of an eye; segmenting a first retinal layer within the volume scan; applying an algorithm for periodic pattern removal of OCT data in the first retinal layer by determining a model of a Fourier transform applicable to a segment of the first retinal layer; and removing transform frequencies associated with the OCT data using the model of the Fourier transform; determining a measure of an amount of axial motion in accordance with a difference of an amount of OCT data captured on a surface of the first retinal layer before and after application of the algorithm for periodic pattern removal; and correcting, the amount of axial motion in the OCT data of the first retinal layer.