Dynamic Color Scale Adjustment for Electro-Anatomical Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cardiac mapping systems lack an effective method to dynamically adjust the color scale for electro-anatomical maps based on actual data distribution, leading to poor resolution and limited information about heart tissue conditions.
Innovation Solution
A method that generates a surface mesh from point cloud data to represent heart geometry, allows users to dynamically adjust the color scale using an interactive histogram, ensuring that the color scale is set within meaningful data ranges, thereby improving the resolution and accuracy of cardiac maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed color scale is used for electro-anatomical maps, then the system is simple to operate, but the resolution and information about heart tissue conditions are limited
Solution Approach 1:
The color scale is transformed from a fixed static configuration to a dynamic adjustable one. Users can interactively modify the color scale parameters (minimum value, maximum value, midpoint) to adapt to different datasets and clinical scenarios, thereby improving measurement precision without requiring complex manual calibration procedures
Solution Approach 2:
The system provides automatic initialization of color scale parameters based on the uploaded dataset. The processor automatically calculates initial minimum, maximum, and midpoint values from the data distribution, allowing the system to serve itself in setting reasonable defaults without requiring extensive user intervention or expertise
2Measurement precision
If the color scale is manually set, then the process is quick, but the color scale may not represent meaningful data ranges
Solution Approach 1:
The system implements feedback mechanisms where user adjustments to the color scale are immediately reflected in the electro-anatomical map visualization. The interactive interface allows users to see real-time changes as they modify parameters, enabling them to fine-tune the color scale to accurately represent meaningful data ranges while minimizing setup time through iterative adjustment
Solution Approach 2:
The system performs preliminary automatic calculation of color scale parameters based on the uploaded dataset before user interaction. This preliminary action establishes a reasonable starting point that already reflects the data distribution, reducing the time users need to spend on adjustment while ensuring accuracy from the outset
Data Source
AI summary
A method for generating an electro-anatomical map to represent an underlying metric associated with heart tissue it is provided. The method comprises receiving, by a mapping system, point cloud data collected for the underlying metric at various locations within the heart; generating, by the mapping system, a surface mesh to represent the geometry of a heart, said surface mesh comprising a plurality of mesh points arranged as a series of interconnected triangles, wherein each mesh point lies on the surface of the heart, and is generated based on the point cloud data; rendering the surface mesh in a viewer application, comprising coloring the mesh points in the surface mesh based on values of the underlying metric associated with each of the mesh points and a color scale; and allowing a user to dynamically adjust the color scale based on a histogram.