Surgical Navigation Coordinate Transformation via Surface Matching
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Solution Overview
Problem
Current surgical navigation systems face challenges in accurately registering a navigation reference coordinate system with an image coordinate system, particularly due to the reliance on multiple tracking points and the complexity of constructing a reliable surface model, which affects the precision of tracking the surgical device relative to the patient.
Innovation Solution
A computer-implemented method determines a transformation between a navigation reference coordinate system and an image coordinate system by receiving multiple picture data sets, identifying feature coordinates, constructing a shape model of the patient surface, and using surface matching techniques to establish a robust registration, potentially without the need for dedicated tracking devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple tracking points and dedicated tracking devices are used for registration, then the reliability of tracking is improved, but the device complexity increases
Solution Approach 1:
The patent combines the patient tracking device with the surface model construction process by using the same picture data sets for both purposes. The feature coordinates extracted from multiple perspectives are used to construct the shape model while simultaneously enabling tracking, eliminating the need for separate dedicated tracking devices and reducing overall system complexity while maintaining tracking reliability.
Solution Approach 2:
The picture data sets and feature extraction process serve multiple functions: they are used both for constructing the patient surface shape model and for enabling tracking of the surgical device. This multi-functional approach allows the system to perform registration and tracking using the same data infrastructure, reducing the need for additional specialized components.
2Manufacturing precision
If multiple picture data sets from different perspectives are used to construct shape model, then the manufacturing precision of surface model is improved, but the loss of time increases
Solution Approach 1:
The patent performs preliminary action by capturing multiple picture data sets from different perspectives before the actual surgical procedure begins. The shape model construction and feature coordinate extraction are completed in advance during the registration phase, allowing the system to establish a precise transformation between coordinate systems beforehand, which then enables rapid tracking during surgery without requiring real-time processing of multiple perspectives.
3Measurement precision
If surface matching techniques are used for registration, then the measurement precision of transformation is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent introduces an intermediary approach by using feature coordinates extracted from multiple perspectives as intermediate data structures. These feature coordinates serve as a bridge between the raw picture data sets and the final surface matching process, simplifying the detection and measurement tasks by breaking down the complex surface matching into manageable steps of feature extraction, coordinate determination, and then matching.
Data Source
AI summary
A technique for determining a transformation between a navigation reference coordinate system (302) for navigation of a surgical device (150) relative to patient image data and an image coordinate system (304) in which the patient image data define a shape of a patient surface is provided. A computer-implemented method implementation of that technique comprises receiving multiple data sets that have been taken from different perspectives of the patient surface. Feature coordinates of multiple features (170) identifiable in the picture data sets are determined from the picture data sets and in the navigation reference coordinate system (302). From the feature coordinates, a shape model of the patient surface in the navigation reference coordinate system (302) is determined. Then, surface matching between the shape model and the shape of the patient surface defined by the patient image data is applied to determine the transformation (T1) between the navigation reference coordinate system (302) and the image coordinate system (304).