2D/3D Registration Using Gradient Contour Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current 2D/3D registration methods in medical imaging face challenges such as inaccurate overlays due to patient movement during interventions, requiring frequent reinitialization and leading to computational inefficiencies and tracking errors, especially in real-time applications.
Innovation Solution
A method that selects contour points directly in the two-dimensional gradient comparison image, avoiding the need for three-dimensional starting point estimation, using depth-aware gradient projection to enhance registration efficiency and accuracy, and employing a multiple resolution scheme to improve computational efficiency and real-time capability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If tracking-based approaches are used to automatically track patient movement during x-ray monitoring, then motion correction can be performed in real-time, but tracking errors accumulate and 2D/3D correspondences are lost due to movement
Solution Approach 1:
The patent performs a new 2D/3D registration at the beginning of each fluoroscopic image sequence to establish accurate initial correspondences between the 3D image dataset and 2D x-ray images. This preliminary registration provides a reliable foundation for subsequent tracking, preventing accumulation of errors that would otherwise degrade registration accuracy over time
Solution Approach 2:
The patent continuously monitors the quality of 2D/3D correspondences during tracking and automatically triggers re-initialization when correspondences are lost or tracking errors accumulate. This feedback mechanism ensures registration accuracy is maintained by resetting the tracking system when it degrades, balancing real-time correction with reliability
2Reliability
If manual re-initialization of 2D/3D registration is performed when misregistration becomes visible, then accurate overlay is restored, but the interventional procedure is interrupted
Solution Approach 1:
The patent implements automatic tracking-based motion correction that continuously updates the 2D/3D registration without requiring manual intervention. The system self-corrects for patient movements by tracking anatomical landmarks and automatically adjusting the overlay, eliminating the need for manual re-initialization and preventing interruptions to the interventional procedure
Solution Approach 2:
The patent maintains continuous tracking of patient movement throughout the fluoroscopic sequence, enabling uninterrupted real-time correction of registration. This continuous action ensures the overlay remains accurate throughout the procedure without pauses for manual re-initialization, maintaining both reliability and procedural efficiency
3Measurement precision
If dense sets of contour points are used in 2D/3D registration, then registration accuracy is improved, but computational overhead increases significantly
Solution Approach 1:
The patent extracts and uses only the most informative contour points from the 3D image dataset that provide the best 2D/3D correspondences in the fluoroscopic images. By selecting a sparse subset of highly discriminative contour points rather than processing all possible points, the method achieves accurate registration with reduced computational overhead
Solution Approach 2:
The patent applies different processing strategies to different regions of the image based on their informational value. Contour points in regions with high contrast and clear anatomical landmarks are prioritized and processed in detail, while regions with low informational value receive minimal processing. This local quality approach maintains registration precision in critical areas while reducing overall computational complexity
Data Source
AI summary
A method includes, following specification of an initial transformation as a test transformation that is to be optimized, determining a 2D gradient x-ray image and a 3D gradient dataset of the image dataset, carrying out, for each image element of the gradient comparison image, a check for selection as a contour point, and determining an environment best corresponding to a local environment of the contour point and extending around a comparison point in the gradient x-ray image for all contour points in the at least one gradient comparison image. Local 2D displacement information is determined by comparing the contour points with the associated comparison points, and motion parameters of a 3D motion model describing a movement of the target region between the acquisition of the image dataset and the x-ray image are determined from the displacement information and a registration transformation describing the registration.