EM Tracker Distortion Correction Using Known Distorter Models
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Solution Overview
Problem
Electromagnetic tracking systems face accuracy issues due to distortion fields caused by surgical tools or other distorters during surgical procedures, which are not adequately compensated for, leading to inaccuracies in tracking anatomical structures and surgical tools.
Innovation Solution
The system measures and models the pose and characteristics of distorters within the electromagnetic field to estimate and correct the distortion field, using methods such as dipole modeling, optical tracking, and robotic posing to determine the distortion field's properties, and optimizes these models based on actual EM field data to improve tracking accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electromagnetic tracking systems are used during surgical procedures, then tracking capability is provided, but distortion fields caused by surgical tools reduce tracking accuracy
Solution Approach 1:
The system performs preliminary characterization of distorters by measuring their pose and electromagnetic characteristics before they significantly affect tracking. Distorter models are created in advance using dipole modeling and optimized based on measured EM field data, allowing the system to prepare correction parameters before accuracy degradation occurs during surgery
Solution Approach 2:
The system continuously monitors the electromagnetic field environment and uses measured EM field data to optimize distorter models in real-time. The distortion field estimates are continuously updated based on feedback from EM trackers, and correction parameters are adjusted dynamically to maintain tracking accuracy despite changing surgical conditions
2Measurement precision
If distortion field corrections are implemented, then tracking accuracy is improved, but system complexity increases due to modeling and optimization requirements
Solution Approach 1:
The system introduces an intermediary computational layer that separates the complex physics of distortion field generation from the tracking correction process. Dipole models serve as simplified intermediaries that capture essential distortion characteristics without requiring full electromagnetic simulation, making the system computationally tractable while maintaining accuracy
Solution Approach 2:
The system transforms the complex distortion field problem into a parameter optimization problem by representing distorters with a small set of key parameters (dipole moment, position, orientation). This parameterization approach reduces computational complexity while preserving the essential physics needed for accurate correction
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of electromagnetic tracking systems by correcting for distortion fields, allowing precise determination of anatomical structure and surgical tool poses during surgeries.
Implementation Method 1
transmitting, via an electromagnetic (EM) emitter, an EM field
Implementation Method 2
data representing an experienced EM field at the EM tracker, the experienced EM field distorted by a distortion field caused by the distorter
Data Source
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AI summary
Systems and methods for correcting experienced EM fields measured at each of one or more EM trackers of an EM tracking system as such measurements are influenced by a known distorter are disclosed herein. An EM emitter may transmit an EM field such that it contains the one or more EM trackers. The system then determines a pose of a distorter within the EM field. The system receives, from each EM tracker, data representing experienced EM fields as distorted by a distortion field caused by the distorter. The system proceeds to determine the distortion field using the pose and a model comprising one or more characteristics of the distorter. The system may first optimize the model. The system calculates data representing corresponding corrected experienced EM fields based on each respective experienced EM field and the determined distortion field at the same location.