Surface Point Sampling With Tissue Validation for Medical Registration
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Solution Overview
Problem
Existing surface-based image registration methods in medical navigation systems face challenges with measurement errors from contact-based methods and inability to acquire points on covered regions using contact-free methods.
Innovation Solution
A method for sampling relevant surface points by determining tissue type and validating each point, discarding non-relevant points, using a computer-aided system to improve surface geometry acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If contact-based surface acquisition methods are used, then points can be acquired on covered regions, but measurement errors occur since points are acquired above or below the actual surface
Solution Approach 1:
The system applies different acquisition methods to different regions based on their properties. Contact-free optical methods are used for exposed skin regions where high precision is needed, while contact-based methods are used for covered regions (e.g., hair, dressings) where accessibility is the priority. The validation step filters out low-quality points from contact-based measurements.
Solution Approach 2:
The system changes the measurement parameters and methods based on the detected surface conditions. By analyzing surface properties (e.g., reflectivity, texture) and procedure requirements, the system dynamically selects between contact-free and contact-based acquisition modes for different body regions.
2Measurement precision
If contact-free surface acquisition methods are used, then measurement accuracy is improved, but points cannot be acquired on covered regions
Solution Approach 1:
The registration device is designed to perform multiple functions: it can operate in contact-free mode for exposed regions and switch to contact-based mode for covered regions. The system universally handles both acquisition methods and integrates them through a unified validation and filtering process.
Solution Approach 2:
The system dynamically adapts its acquisition strategy based on real-time detection of surface conditions and procedure requirements. The validation parameters and filtering thresholds are adjusted dynamically to optimize the mix of contact-free and contact-based points for each specific surgical procedure.
3Productivity
If all surface points are collected without validation, then data collection is simple, but distortion occurs and registration precision is reduced
Solution Approach 1:
The system performs preliminary validation of surface points during the acquisition phase itself. Each point is evaluated against validation criteria (e.g., surface normal consistency, curvature thresholds, tissue type matching) before being added to the final dataset, preventing the accumulation of low-quality points that would distort the registration.
Solution Approach 2:
The validation process provides feedback on point quality, allowing the system to adjust acquisition parameters in real-time. Points that fail validation trigger re-acquisition or parameter adjustment, ensuring that only high-quality points contribute to the final registration while maintaining efficient data collection.
Data Source
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AI summary
A method and a registration device for sampling relevant surface points of a subject for a medical navigation system is presented. In particular, from a plurality of surface points of the subject, relevant surface points are accepted and non-relevant surface points are discarded. One technical effect of the invention is that the surface geometry acquisition of a subject can be improved. For this purpose, additional information of the surface points is acquired and assigned to the respective surface point for validating each surface point.