Ophthalmic Data Processing for Lissajous Motion Correction
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Solution Overview
Problem
Existing ophthalmic imaging techniques face challenges in effectively correcting motion artifacts induced by eye movements during scanning, particularly in Lissajous scanning, which affects the quality of ophthalmic data acquisition.
Innovation Solution
A method and apparatus that processes ophthalmic data by applying a two-dimensional pattern with intersecting cycles, generating position history data to correct for eye movement, and employing a configuration that includes a fundus camera unit, OCT unit, and arithmetic and control unit to enhance data processing and imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Lissajous scanning is used to correct motion artifacts, then image quality is improved, but the complexity of data processing increases
Solution Approach 1:
The patent divides the complex Lissajous scanning data into multiple B-scan groups that can be independently processed. Each B-scan group corresponds to a specific angular range and can be registered separately, reducing the overall computational complexity while maintaining image quality through localized motion correction
Solution Approach 2:
The patent introduces angular dimension (θ) as an additional parameter for organizing and processing OCT data. By grouping B-scans according to their angular positions in the Lissajous pattern, the system creates a new dimensional framework that simplifies motion artifact correction and enables more efficient data registration compared to traditional sequential processing
2Measurement precision
If multiple B-scans are averaged to improve signal-to-noise ratio, then imaging quality is improved, but the acquisition time increases
Solution Approach 1:
The patent applies partial averaging by selectively grouping and averaging only those B-scans that fall within specific angular ranges and meet certain quality criteria. This partial averaging approach improves signal-to-noise ratio for critical regions while avoiding the time penalty of averaging all collected data, thus balancing image quality with acquisition efficiency
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
The solution effectively corrects motion artifacts, enabling high-quality imaging and data processing with improved registration and alignment, resulting in accurate ophthalmic data acquisition.
Implementation Method 1
OCT is a technique based on low-coherence interferometry, and typically utilizes probe light (measurement light) in the near-infrared region
Implementation Method 2
capable of measuring and imaging light scattering media at a micrometer level or higher resolution
Implementation Method 3
The scanning imaging is a technique of collecting data by projecting beams sequentially onto a plurality of positions of a sample and constructing an image of the sample from the collected data
Data Source
AI summary
A method of processing ophthalmic data of some embodiment examples includes preparing a data set acquired by applying optical scanning of a two-dimensional pattern to a subject's eye. The two-dimensional pattern of the optical scanning includes a series of cycles that intersects each other. The method further includes generating position history data based on the data set. The position history data represents a temporal change in a position of the subject's eye.