Multi-Rigid Magnetic Registration for Deformed Lung Navigation
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Solution Overview
Problem
Existing bronchoscopy systems face limitations in navigating deep into the lungs due to bronchoscope size and challenges in distinguishing luminal passageways from solid tissue in two-dimensional CT or fluoroscopic images, necessitating improved registration methods for three-dimensional navigation.
Innovation Solution
A method and system for multi-rigid registration of electromagnetic navigation with a patient's CT scan volumetric model, utilizing a weighting metric to dynamically determine the most accurate registration based on lung regions, accounting for lung deformation during procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single rigid registration method is used to align electromagnetic navigation with CT scan, then the registration process is simple and fast, but navigation accuracy deteriorates in deformed lung regions
Solution Approach 1:
The patent divides the lung volume into multiple rigid regions, each with its own registration transformation. Instead of applying a single global registration, the system performs segmented rigid registrations where each region can be independently transformed, allowing accurate navigation even when lung deformation occurs in specific areas while maintaining overall system manageability.
2Measurement precision
If multiple registrations are generated for different lung regions, then navigation accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary rigid registrations for all lung regions before the actual navigation procedure. These pre-computed registrations are stored and ready for use, eliminating the need for real-time computation during navigation. When navigating, the system simply selects the appropriate pre-computed registration based on the current lung region, maintaining high accuracy while minimizing processing time.
3Measurement precision
If manual registration is used based on visual identification of branching points, then the system remains simple to operate, but registration precision deteriorates due to user subjectivity
Solution Approach 1:
The patent employs automatic rigid registration algorithms that perform the alignment process without requiring manual intervention. The system automatically identifies corresponding features between the electromagnetic navigation data and CT scan, computes the transformation matrices, and applies the registrations. This self-service approach eliminates user subjectivity while maintaining operational simplicity through automated workflows.
Data Source
AI summary
Devices, systems, methods, and computer-readable media for registering an electromagnetic registration of a luminal network to a 3D model of the luminal network include accessing a 3D model of a luminal network based on computed tomographic (CT) images of the luminal network, selecting a plurality of reference points within the 3D model of the luminal network, obtaining a plurality of survey points within the luminal network, dividing the 3D model of the luminal network and the luminal network into a plurality of regions, assigning a plurality of weights to the plurality of regions, determining an alignment of the plurality of reference points with the plurality of survey points based on the plurality of weights, and generating a registration based on the alignment, the registration enabling conversion of the plurality of survey points within the luminal network to points within the 3D model of the luminal network.