Surgical Navigation Accuracy Verification Using X-Ray Instrument Segmentation
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Solution Overview
Problem
Current electromagnetic navigation systems in medical applications rely on subjective methods for assessing accuracy, which can vary between surgeons and may compromise surgical effectiveness due to potential inaccuracy.
Innovation Solution
A method and system that automate the verification of surgical navigation system accuracy by acquiring X-ray images, segmenting surgical instruments, computing the distance between predicted and actual instrument locations, and alerting users if the distance exceeds a threshold value, using edge detection and pattern recognition algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If subjective visual comparison method is used to assess navigation accuracy, then the system operation remains simple, but the measurement precision and reliability of accuracy assessment deteriorate due to surgeon variability
Solution Approach 1:
The system automatically performs accuracy verification without requiring surgeon intervention. The computer system independently compares predicted and actual instrument locations, computes navigation errors, and generates reports, allowing the system to self-verify its own accuracy rather than relying on human subjectivity.
Solution Approach 2:
The patent replaces the mechanical/visual comparison process with automated computational algorithms. Instead of surgeons visually comparing images, the system uses image processing, segmentation, and computational geometry to automatically measure and compare positions, substituting human visual assessment with objective computer-based measurement.
2Measurement precision
If automated accuracy verification system is implemented, then the measurement precision and reliability of accuracy assessment improve, but the device complexity increases
Solution Approach 1:
The accuracy verification system is integrated into the existing navigation system architecture, allowing the same hardware and software platform to perform both navigation and verification functions. The system reuses existing image acquisition, tracking, and display components while adding verification capabilities, thereby reducing overall system complexity compared to separate dedicated verification systems.
Solution Approach 2:
The system creates a digital copy or representation of the surgical field using image processing and segmentation algorithms. By working with computational models and virtual representations rather than physical measurements, the system simplifies the verification process and reduces the need for complex physical measurement apparatus.
3Reliability
If automated accuracy verification is performed, then the reliability of navigation system performance improves, but the loss of time during surgical procedure increases
Solution Approach 1:
The system performs accuracy verification before the surgical procedure begins or at scheduled intervals during the procedure. By conducting verification in advance or at predetermined times rather than continuously or reactively, the system ensures navigation accuracy is confirmed without causing delays during critical surgical operations.
Solution Approach 2:
The accuracy verification operates continuously in the background during navigation operations, utilizing available computational resources without interrupting the surgical workflow. The system maintains verification readiness throughout the procedure, ensuring navigation reliability is continuously monitored without requiring discrete time-consuming verification steps that would halt surgery.
Data Source
AI summary
Certain embodiments of the present invention provide for a system and method for assessing the accuracy of a surgical navigation system. The method may include acquiring an X-ray image that captures a surgical instrument. The method may also include segmenting the surgical instrument in the X-ray image. In an embodiment, the segmenting may be performed using edge detection or pattern recognition. The distance between the predicted location of the surgical instrument tip and the actual location of the surgical instrument tip may be computed. The distance between the predicted location of the surgical instrument tip and the actual location of the surgical instrument tip may be compared with a threshold value. If the distance between the predicted location of the surgical instrument tip and the actual location of the surgical instrument tip is greater than the threshold value, the user may be alerted.


