Medical Robotic Navigation with Physiological Noise Detection
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Solution Overview
Problem
Current techniques for navigating tubular networks, such as those in bronchoscopy, face challenges with inaccurate motion estimation of medical devices within the body, leading to incorrect localization and misleading information for physicians during surgical procedures.
Innovation Solution
A medical robotic system that uses image sensors to detect points of interest, identify locations, and track changes in the device's position within the luminal network, combining data from multiple image frames to enhance navigation accuracy through the integration of EM tracking and 3D modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If motion estimation is performed based on location and orientation change of the device, then navigation capability is provided, but measurement precision deteriorates due to inaccurate localization
Solution Approach 1:
The patent introduces an intermediary reference frame system that mediates between the device's mechanical position and the physiological environment. By detecting physiological noise through image analysis and transforming device coordinates into a noise-compensated reference frame, the system achieves accurate localization despite physiological movements. The intermediary reference frame acts as a buffer that separates mechanical position from physiological variability.
Solution Approach 2:
The patent replaces purely mechanical position tracking with an image-based detection system. Instead of relying solely on mechanical encoders and orientation sensors, the system uses image sensors to detect anatomical landmarks and physiological movements, then computationally determines device position. This substitution of mechanical tracking with optical/image-based measurement enables compensation for physiological noise.
2Ease of operation
If 3D models are generated from CT scans to provide visual reference, then navigation guidance is improved, but reliability deteriorates due to mismatch between static model and dynamic physiological environment
Solution Approach 1:
The patent transforms the static 3D model into a dynamic reference system that adapts to physiological changes. By continuously detecting physiological noise through image analysis and updating the reference frame accordingly, the system maintains correspondence between the visual model and the living physiological environment. The reference frame becomes dynamic, adjusting in real-time to respiratory and cardiac movements.
Solution Approach 2:
The patent implements a feedback loop where image data from the physiological environment is continuously analyzed to detect noise patterns, which then feed back into updating the reference frame. This closed-loop system ensures the 3D model remains synchronized with actual physiological conditions, with the feedback mechanism correcting drift between model and reality through real-time image-based detection.
Data Source
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AI summary
Provided are robotic systems and methods for navigation of luminal network that detect physiological noise. In one aspect, the system includes a set of one or more processors configured to receive first and second image data from an image sensor located on an instrument, detect a set of one or more points of interest the first image data, and identify a set of first locations and a set of second location respectively corresponding to the set of points in the first and second image data. The set of processors are further configured to, based on the set of first locations and the set of second locations, detect a change of location of the instrument within a luminal network caused by movement of the luminal network relative to the instrument based on the set of first locations and the set of second locations.