Gradient Search for Laser Surgical Imaging
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Solution Overview
Problem
Current imaging techniques, such as optical coherence tomography, require full-field scanning to create detailed three-dimensional images, which is wasteful and time-consuming, especially in applications where only specific points or features need to be identified, like in ophthalmic surgeries, as they store and process unnecessary data points.
Innovation Solution
A gradient search method that determines the coordinate and direction of a boundary or feature in a target region by selecting specific locations based on the gradient direction, allowing for local sensing and measurement without full-field scanning, thereby reducing data capture and processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full-field scanning is performed to create detailed three-dimensional images, then imaging completeness and resolution are improved, but processing time and data storage requirements increase
Solution Approach 1:
The patent extracts only the essential information needed for surgical guidance (boundary coordinates and gradient directions) from the full field, rather than processing complete three-dimensional images. This is achieved by scanning only along boundary loops and performing local gradient calculations at selected points, eliminating unnecessary data capture and processing while maintaining sufficient precision for identifying extrema points.
Solution Approach 2:
The patent applies local quality by performing detailed scanning and analysis only at specific locations (boundary loops and selected points within regions) rather than uniformly across the entire field. The gradient search is conducted locally at discrete points, and imaging is performed locally along boundary loops, concentrating computational resources where they are most needed for surgical reference point identification.
2Loss of information
If full-field scanning is performed to create detailed three-dimensional images, then imaging completeness is improved, but data storage requirements increase
Solution Approach 1:
The patent extracts only the critical geometric information (boundary coordinates and gradient directions) required for surgical planning, discarding redundant data from complete volumetric imaging. By scanning only along boundary loops and performing localized gradient searches, the system captures essential anatomical features while storing minimal data, eliminating the need to store and process entire three-dimensional image datasets.
3Productivity
If local gradient search is performed instead of full-field scanning, then processing time is reduced, but measurement precision may be compromised
Solution Approach 1:
The patent performs preliminary scanning along boundary loops to identify region boundaries and select candidate points for gradient search before conducting the full extremum search. This preliminary action establishes the search space and guides subsequent local gradient calculations, ensuring that precision is maintained at critical locations while avoiding unnecessary scanning in less relevant areas.
Solution Approach 2:
The patent employs feedback by using gradient direction information from local searches to iteratively refine the search for extrema points. The gradient calculations at selected points provide feedback that guides the identification of boundary extrema and internal extrema, progressively improving precision through iterative refinement rather than requiring complete initial scanning of the entire field.
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 method significantly reduces processing time and resource usage by focusing on relevant data points, enabling faster identification of extremum points, such as the apex of the cornea or cataract, essential for timely ophthalmic surgeries, and can determine extremum points in under 10 seconds.
Implementation Method 1
Optical Coherence Tomography (OCT) is one of the many methods to create three dimensional images and extract structural information of materials. This is usually done by scanning an optical beam over a target region or surface and then analyzing the spatial, spectral and temporal characteristics of the scattered and returned light.
Data Source
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AI summary
Techniques and systems for gradient search are provided based on sensing or measuring at selected locations of a target object without performing full-field sensing or measuring over the entire field of the target object. Search methods are provided to include determining a coordinate of a boundary of a region in relation to a loop in a proximity of a first location, determining a direction of a gradient of the coordinate corresponding to the first location, and selecting a second location based on the determined direction. A search system can be implemented to include an imaging system to determine a coordinate of a feature of an object on a loop in a proximity of a first location, and a controller, coupled to the imaging system, to determine a direction of a gradient of the coordinate corresponding to the first location, and to select a second location based on the determined direction.