Surgical Camera Tracking for Phantom Marker Filtering
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Solution Overview
Problem
Camera tracking systems in computer-assisted surgery navigation face challenges in accurately registering stray markers due to the presence of phantom markers, which can lead to erroneous navigation when the patient reference array shifts, especially during procedures like spinal fusion.
Innovation Solution
The camera tracking system employs operations to classify stray markers as 'assigned', 'unknown', and 'phantom' status, utilizing epipolar ambiguity and threshold distances to filter out phantom markers, ensuring accurate registration of surveillance markers by designating them as 'assigned' or 'unknown' status based on consistent visibility and spatial relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the camera tracking system uses standard marker registration methods, then the registration process is simple, but phantom markers cause erroneous navigation and reduce reliability
Solution Approach 1:
The patent segments the marker registration process into distinct classification stages: detecting stray markers, determining epipolar ambiguity status, identifying phantom markers through 3D location analysis, and separating them from valid surveillance markers. This segmentation allows the system to handle phantom markers systematically without compromising overall navigation reliability.
Solution Approach 2:
The patent introduces an intermediary classification system that acts as a mediator between raw marker detection and final navigation decisions. By inserting epipolar ambiguity analysis and phantom marker identification as intermediate steps, the system filters out erroneous markers before they can affect navigation accuracy.
2Productivity
If the system registers all detected stray markers as surveillance markers, then the registration process is fast, but phantom markers lead to incorrect navigation
Solution Approach 1:
The patent performs preliminary actions by detecting and classifying phantom markers before final surveillance marker registration. The system proactively identifies epipolar ambiguous markers and estimates their 3D locations to determine if they are phantom markers, preventing incorrect registrations before they occur.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors marker detections, analyzes epipolar ambiguity, and adjusts registration decisions based on phantom marker identification results. This feedback loop ensures that only valid surveillance markers are registered while phantom markers are excluded.
3Measurement precision
If the system implements comprehensive phantom marker detection, then navigation accuracy improves, but the complexity of marker status classification increases
Solution Approach 1:
The patent applies local quality by focusing computational resources on specific critical aspects: epipolar ambiguity analysis for problematic markers and 3D location estimation for phantom marker identification. Rather than uniformly processing all markers with equal complexity, the system applies sophisticated analysis only where needed to distinguish phantom from valid markers.
Data Source
AI summary
A camera tracking system for computer assisted navigation during surgery. Operations identify stray markers in a frame of tracking data from tracking cameras, and identify stray markers of a reference array. Stray markers of the reference array are designated assigned status and, otherwise, designated unknown status. The operations designate other of the assigned status stray markers and any of the unknown status stray markers along a same epipolar line of the tracking cameras as one of the assigned status stray markers as being epipolar ambiguous status. For each one of the epipolar ambiguous status stray markers, the operations estimate 3D locations where phantom markers can appear in the frame based on epipolar ambiguity of the tracking cameras when determining location of the one of the epipolar ambiguous status stray markers. The operations designate the unknown status stray markers within a threshold distance of the estimated 3D locations of phantom markers as being phantom status.