ICE Catheter Image Navigation for Autonomous Target View Guidance
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Solution Overview
Problem
ICE (intracardiac echocardiography) is underutilized in cardiac electrophysiology procedures due to complexity, limited field-of-view, requirement of two operators, and extensive training, hindering its effective use for therapy guidance and adverse event detection.
Innovation Solution
A robotic catheter navigation system utilizing machine learning and image registration techniques to automatically navigate catheters to target views, leveraging preoperative medical images, saved medical images, and standard anatomical views, with reinforcement learning for precise catheter movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual ICE procedures are performed with human operators, then flexibility and adaptability are maintained, but device complexity and operational difficulty increase significantly
Solution Approach 1:
The system performs self-navigation using autonomous machine learning models that automatically determine catheter movement actions based on image analysis, eliminating the need for manual operator control and reducing operational complexity
Solution Approach 2:
Manual mechanical manipulation of the catheter by operators is replaced with an automated robotic navigation system that uses computer vision and reinforcement learning to control catheter movements, substituting human skill with algorithmic control
2Ease of operation
If automated navigation is implemented using machine learning, then ease of operation improves, but measurement precision and navigation accuracy face challenges
Solution Approach 1:
The system continuously receives real-time ICE images, compares current catheter position with target position, and adjusts navigation actions based on image similarity metrics and reinforcement learning feedback to maintain precise navigation
Solution Approach 2:
The system performs preliminary image registration between preoperative medical images and intraoperative ICE images before navigation begins, establishing an accurate spatial mapping that enables precise target view identification and navigation planning
3Measurement precision
If image registration between preoperative and intraoperative images is performed, then navigation accuracy to target views improves, but processing time and computational complexity increase
Solution Approach 1:
Image registration is performed as a preliminary step before navigation begins, establishing the spatial transformation once to enable rapid subsequent navigation decisions without repeated heavy computation
Solution Approach 2:
The system focuses registration and image processing on relevant anatomical regions and key features rather than processing entire images, reducing computational burden while maintaining navigation accuracy
Data Source
AI summary
Systems and methods for automatically navigating a catheter in a patient are provided. An image of a current view of a catheter in a patient is received. A set of actions of a robotic navigation system for navigating the catheter from the current view towards a target view is determined using a machine learning based network. The catheter is automatically navigated in the patient from the current view towards the target view using the robotic navigation system based on the set of actions.