2D-3D Image Registration Initialization for Faster Convergence
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing 2D-3D registration methods in robot-assisted surgery require a large number of iterations to converge, leading to time delays and potential failure, which hinders efficient image guidance.
Innovation Solution
The method initializes the computational configuration to align simulated and actual x-rays closely before starting iterations, improving convergence and reducing processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative methods are used to generate DRRs until they match actual x-ray images, then registration accuracy is improved, but the number of iterations required increases leading to time delays and potential convergence failure
Solution Approach 1:
The patent applies preliminary action by performing an initial alignment step before the iterative optimization process. The computational configuration is initialized to align simulated and actual x-rays closely before starting iterations, which reduces the number of iterations needed and accelerates convergence while maintaining registration accuracy
2Measurement precision
If iterative methods are used to minimize cost function by adjusting parameters, then registration accuracy is improved, but the incidence of failure to converge increases
Solution Approach 1:
The patent applies preliminary action by performing an initial alignment step before the iterative optimization process. The computational configuration is initialized to align simulated and actual x-rays closely before starting iterations, which reduces the number of iterations needed and accelerates convergence while maintaining registration accuracy
3Measurement precision
If a large number of iterations are performed to achieve successful match, then registration accuracy is improved, but processing efficiency deteriorates
Solution Approach 1:
The patent applies preliminary action by performing an initial alignment step before the iterative optimization process. The computational configuration is initialized to align simulated and actual x-rays closely before starting iterations, which reduces the number of iterations needed and accelerates convergence while maintaining registration accuracy
Data Source
AI summary
A method for registration of digital medical images is provided. The method includes the step of storing a 3D digital medical image having a 3D anatomical feature and a first coordinate system and storing a 2D digital medical image having a 2D anatomical feature and a second coordinate system. The method further includes the steps of storing a placement of a digital medical object on the 3D digital medical image and the 2D digital medical image and generating a simulated 2D digital medical image from the 3D digital medical image, wherein the simulated 2D digital medical image comprises a simulated 2D anatomical feature corresponding to the 3D anatomical feature. The 2D anatomical feature is compared with the simulated 2D anatomical feature until a match is reached and a registration of the first coordinate system with the second coordinate system based on the match is determined.