Dynamic Mapping Point Filtering for 3D Anatomical Map Registration
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Solution Overview
Problem
Current medical imaging technologies face challenges in accurately registering mapping points from a medical probe to a pre-acquired three-dimensional image of a body cavity, often resulting in significant errors that affect the quality of the anatomical map generated.
Innovation Solution
A method and system that involve acquiring an image of a body cavity, receiving multiple sets of mapping points from a probe with a location sensor, performing registrations between the mapping points and the image, and generating an updated three-dimensional anatomical map by filtering points based on error thresholds, thereby improving the alignment and accuracy of the map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple mapping points are collected from the probe to improve map coverage, then the quantity of mapping points increases, but the cumulative error value increases reducing registration quality
Solution Approach 1:
The system performs a preliminary registration process before final map generation. It first registers an initial set of mapping points to create a preliminary anatomical map, then uses this preliminary map to guide subsequent point collection and registration, thereby improving overall registration quality while maintaining map coverage
Solution Approach 2:
The system implements a feedback mechanism where the registration quality of previously collected mapping points is evaluated, and this information is used to adjust the registration process for subsequent points. The system uses the preliminary map and its associated error values to guide the registration of additional points, ensuring that registration quality is maintained even as map coverage increases
2Loss of information
If all mapping points are included in the anatomical map to maintain data completeness, then information loss is minimized, but the cumulative error value increases reducing overall map accuracy
Solution Approach 1:
The system applies local quality by assigning different weights or levels of confidence to different mapping points based on their individual error values. High-quality points with low error values are given more weight in map generation, while low-quality points with high error values are either down-weighted or excluded, thereby maintaining data completeness where appropriate while improving overall map accuracy
Solution Approach 2:
The system changes the parameter of point inclusion by dynamically adjusting which mapping points are included in the final anatomical map based on their error values relative to the cumulative error threshold. This allows the system to maintain data completeness for points below the threshold while excluding points that would degrade overall map accuracy
3Measurement precision
If a strict point error threshold is applied to filter mapping points, then map accuracy is improved by excluding high-error points, but the quantity of mapping points decreases affecting map coverage
Solution Approach 1:
The system performs preliminary registration and error evaluation on an initial set of mapping points before applying the strict error threshold. This preliminary step allows the system to identify which points meet the accuracy criteria and plan subsequent point collection to achieve adequate coverage with high-quality points
Data Source
AI summary
A method including acquiring a body cavity image and receiving first and second sets of mapping points from a probe inserted into the cavity. A first registration, having a first cumulative error value, is performed between the first set's mapping points and the image, each of the first set's mapping points having a respective first point error value, and a 3D anatomical map is generated including the first set's mapping points whose respective first point error values are less than a specified threshold. A second registration is performed between the received mapping points and the image, each of the received mapping points having a respective second point error value, the second registration having a second cumulative error value lower than the first cumulative error value, and an updated 3D anatomical map is generated including the received mapping points whose respective second point error values are less than the specified threshold.