Tomographic Eye Imaging Displacement Correction
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Solution Overview
Problem
Current tomographic imaging methods for eyes face challenges in accurately correcting displacement and magnification deviations among multiple images, leading to distorted and noisy images, which are difficult to address with general parallel and rotation movements.
Innovation Solution
A method that involves obtaining a displacement distribution for each A-scan among multiple tomographic images and correcting displacements based on this distribution, along with correcting magnification deviations by adjusting the scan width, allowing for precise alignment and reconstruction of clear, noise-reduced images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If general parallel and rotation movements are used to correct displacement among multiple tomographic images, then the correction process is simple, but the images remain distorted and noisy due to magnification deviations
Solution Approach 1:
The patent divides the tomographic image into multiple divided areas and calculates displacement and magnification deviation separately for each area. This segmentation allows precise correction of local variations while maintaining overall image coherence, resolving the contradiction between simple correction processes and accurate alignment.
Solution Approach 2:
The patent applies different correction parameters (displacement and magnification deviation) to different divided areas of the image. By treating each area with its own specific correction values, the system achieves high precision alignment without requiring a complex global correction approach.
2Object-affected harmful factors
If multiple tomographic images are obtained for averaging noise, then the noise reduction effect is improved, but displacement and magnification deviations cause distortion in the averaged image
Solution Approach 1:
The patent performs displacement and magnification deviation correction on each divided area before averaging the multiple tomographic images. By preliminarily aligning and correcting each image, the subsequent averaging process produces a clear, distortion-free result while maintaining noise reduction benefits.
3Device complexity
If displacement correction is performed without considering magnification deviation, then the correction process is simpler, but the reconstructed three-dimensional data becomes distorted
Solution Approach 1:
The patent segments the correction process into two distinct calculations for each divided area: displacement correction and magnification deviation correction. This segmentation makes the complex process manageable while ensuring both parameters are addressed for accurate three-dimensional reconstruction.
Solution Approach 2:
The patent introduces magnification deviation as an additional correction parameter alongside displacement. By changing the correction model to include this second parameter, the system achieves accurate three-dimensional data reconstruction without excessive complexity.
Data Source
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AI summary
A method for capturing a tomographic image of an eye includes: obtaining a plurality of tomographic images of an examinee's eye by an optical scanning; obtaining a displacement distribution that is a distribution of a displacement for each A-scan among the plurality of tomographic images; and correcting a displacement among the tomographic images based on the displacement distribution.