Intraoperative Surface-Based Registration for Spinal Navigation
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Solution Overview
Problem
Conventional surgical navigation methods face inaccuracies when dealing with multiple spinal levels due to global and local motion, requiring frequent re-registration and disrupting clinical workflow, especially when navigating anatomical bodies with independent degrees of freedom.
Innovation Solution
The system dynamically selects and updates multiple registration transforms for different surface regions, allowing for continuous accuracy by recalculating and applying registration transforms independently for each anatomical body, even in the presence of motion, using surface detection systems and tracking technologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single global registration transform is used for multiple spinal levels, then the device complexity is reduced, but navigation accuracy deteriorates due to global and local motion between anatomical bodies
Solution Approach 1:
The patent divides the anatomical body into multiple independent rigid bodies (e.g., individual vertebrae or spinal levels), each with its own independent registration transform. This segmentation allows each body to be tracked separately, maintaining navigation accuracy even when relative motion occurs between bodies, while avoiding the need for a single complex global transform that would fail to account for local movements.
Solution Approach 2:
The system dynamically updates registration transforms for each rigid body independently based on real-time tracking data. Instead of using a static global transform, the system adapts to motion by continuously recalculating local transforms, allowing the navigation system to remain accurate despite changes in anatomical configuration during the procedure.
2Reliability
If registration transforms are updated frequently to maintain accuracy during motion, then navigation reliability is improved, but loss of time increases due to frequent re-registration operations
Solution Approach 1:
The system performs preliminary registration for each rigid body before the procedure begins, establishing initial transforms that can be quickly updated during the procedure. This preliminary setup reduces the computational burden during real-time updates, allowing frequent refreshes of navigation accuracy without significant time loss during critical surgical moments.
Solution Approach 2:
The registration transforms are updated continuously or near-continuously during the procedure based on real-time tracking data, rather than through discrete re-registration operations. This continuous updating maintains navigation reliability throughout the procedure while minimizing interruptions to the surgical workflow, as the system automatically adjusts transforms without requiring manual re-registration interventions.
3Measurement precision
If multiple independent registration transforms are used for different surface regions, then navigation accuracy is maintained across multiple spinal levels, but device complexity increases
Solution Approach 1:
The anatomical body is segmented into multiple rigid bodies, each with its own registration transform. This segmentation enables independent tracking of each body, maintaining navigation accuracy across multiple spinal levels or anatomical regions. The system manages this complexity through automated tracking and transformation algorithms that handle multiple transforms simultaneously without requiring manual intervention for each body.
Solution Approach 2:
The registration system is designed with universal algorithms and data structures that can handle any number of rigid bodies and surface regions. The same core transformation and tracking mechanisms are applied uniformly across all bodies, allowing the system to scale from single-level to multi-level procedures without proportionally increasing operational complexity. The system treats each rigid body using the same multi-functional framework.
Data Source
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AI summary
Various example embodiments of the present disclosure provide systems and methods for performing image-guided navigation during medical procedures using intraoperative surface detection. A surface detection device is employed to obtain intraoperative surface data characterizing multiple surface regions of a subject. Pre- operative volumetric image data is registered to each surface region, providing per- surface-region registration transforms. In some example embodiments, navigation images may be generated intraoperatively based on the dynamic selection of a suitable registration transform. For example, a registration transform for generating navigation images may be dynamically determined based on the proximity of a tracked surgical tool relative to the surface regions. In an alternative example embodiment, multiple navigation images may be displayed, wherein each navigation image is generated using a different registration transform.