Electrophysiological Map Generation via 3D Texture Normalization
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Solution Overview
Problem
Existing algorithms for generating electrophysiological maps of geometric structures, such as the heart, face interpolation issues and become computationally expensive when dealing with large numbers of diagnostic landmark points, resulting in incomplete and suboptimal triangulations.
Innovation Solution
A system and method that involves acquiring location data points and electrical information at diagnostic landmark points, creating 3D texture regions for weighted physiological metrics and total weights, additively blending color values into voxels, normalizing them, and generating an electrophysiological map from a normalized 3D texture map, which prevents interpolation problems and allows for more detailed mapping with large facets while maintaining efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If heuristic algorithms are used for interpolating and rendering contact maps, then the implementation is simple, but the triangulations become incomplete and suboptimal when average distance between diagnostic landmark points is near or below average distance between geometry points
Solution Approach 1:
The patent changes the fundamental parameter of the interpolation approach by switching from heuristic methods to a partial differential equation (PDE)-based continuous field method. This allows the system to handle cases where diagnostic landmark points are densely spaced by treating the problem as a continuous mathematical field rather than discrete point interpolation, thereby maintaining triangulation quality across all point densities.
Solution Approach 2:
The patent replaces the mechanical/heuristic interpolation algorithm with a mathematical physics-based approach using partial differential equations. This substitution enables the system to naturally handle complex geometric relationships and dense point distributions that heuristic methods cannot resolve properly, improving triangulation accuracy without sacrificing computational feasibility.
2Measurement precision
If large numbers of diagnostic landmark points are collected, then the map detail and resolution improve, but the computational cost becomes expensive
Solution Approach 1:
The patent transitions from discrete point-based interpolation to a continuous field representation using partial differential equations. This dimensional shift allows the system to efficiently handle large numbers of diagnostic landmark points by treating them as samples of an underlying continuous physiological field, thereby maintaining high map resolution without proportionally increasing computational cost.
Solution Approach 2:
The patent changes the mathematical formulation from discrete heuristic interpolation to a continuous PDE-based system. This parameter change enables the efficient processing of large datasets by leveraging the mathematical properties of continuous fields, where the computational complexity scales more favorably with the number of input points compared to traditional discrete interpolation methods.
3Productivity
If facet size is increased to reduce computational load, then processing efficiency improves, but the electrophysiological map loses detail and accuracy
Solution Approach 1:
The patent fundamentally changes the rendering parameter from discrete facet-based triangulation to a continuous field solution of partial differential equations. This allows the system to maintain high electrophysiological detail regardless of facet size because the continuous mathematical field inherently preserves fine-scale variations without requiring fine geometric discretization, thus decoupling processing efficiency from map detail.
Data Source
AI summary
The present disclosure provides systems and methods for generating an electrophysiological map of a geometric structure. The system includes a computer-based model construction system configured to acquire electrical information at a plurality of diagnostic landmark points, assign a color value, based on the acquired electrical information, to each of the diagnostic landmark points, create a first 3D texture region storing floats for a weighted physiological metric, create a second 3D texture region storing floats for a total weight, for each diagnostic landmark point, additively blend the color value of the diagnostic landmark point into voxels of the first 3D texture region that are within a predetermined distance, normalize the colored voxels using the second 3D texture region to generate a normalized 3D texture map, generate the electrophysiological map from the normalized 3D texture map and a surface of the geometric structure, and display the generated electrophysiological map.