Automatic Mesh Reshaping for Cardiac Electroanatomical Map Accuracy
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Solution Overview
Problem
Manual editing of cardiac electroanatomical maps is time-consuming and prone to errors, causing locations marked for treatment to be obscured, leading to inaccuracies in the mapping of cardiac cavity surfaces during ablation procedures.
Innovation Solution
A processor-generated method that updates the volume map by removing erroneous mapped locations, projecting treatment locations onto the surface, and using a 'ball rolling' algorithm to reconstruct the cavity surface, ensuring that treatment locations are visible and accurately represented on the map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual editing methods are used to update the volume map and expose treatment locations, then the map can be corrected, but the editing process becomes time-consuming and error-prone
Solution Approach 1:
The system performs automatic mesh reshaping where the algorithm itself identifies and corrects the hiding of treatment locations without requiring manual intervention. The processor automatically detects when treatment locations are obscured by the volume map surface and performs the necessary mesh modifications to expose them, making the system self-correcting and eliminating time-consuming manual editing while maintaining high accuracy
Solution Approach 2:
The patent replaces manual mechanical editing operations with an automated computational algorithm. Instead of requiring operators to manually adjust the volume map mesh to expose treatment locations, the system uses a processor-executed algorithm that automatically performs the mesh reshaping operations, substituting human manual work with automated computational processing that is both faster and more consistent
2Loss of information
If the volume map is updated to expose internal treatment locations, then treatment locations become visible, but the complexity of the mesh processing increases
Solution Approach 1:
The patent segments the mesh processing into distinct automated stages: first identifying treatment locations within the volume map, then determining which mesh elements obscure these locations, and finally selectively modifying only the necessary mesh portions. This segmentation of the processing task into discrete automated steps manages complexity by breaking down the overall operation into smaller, more manageable computational tasks that can be executed systematically
Solution Approach 2:
The system introduces an automated algorithm as an intermediary between the raw volume map data and the final displayed map. This intermediary processor executes the mesh reshaping logic, acting as a mediator that automatically handles the complex transformations required to expose treatment locations without requiring direct human intervention in the complex mesh manipulation process
Data Source
AI summary
A method includes receiving or generating a volume map of at least a portion of a cavity of an organ of a body including a plurality of mapped locations, and a point cloud of locations in the cavity marked for treatment. The volume map is updated by removing a portion of the mapped locations, so that the locations marked for treatment fall on a surface of the volume map. Using the updated volume map, a map of at least a portion of the cavity is generated, the map including the locations marked for treatment. The map is displayed to user.