Four-Chamber Heart Model Using Open Mesh Resampling
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Solution Overview
Problem
Current methods for generating statistical heart models from 3D medical images face challenges such as inaccurate anatomy representation, excessive detail, and slow optimization processes due to large numbers of variables in dense representations, as well as the difficulty in establishing point correspondence in 3D data without natural ordering of mesh points.
Innovation Solution
A method for generating a four-chamber statistical heart model by editing and deforming initial meshes based on anatomical landmarks like valves, using resampling techniques to establish mesh point correspondence, and creating open meshes that explicitly model valves and cusp points, allowing for automatic heart segmentation without the need for time-consuming 3D shape registration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If surface-based heart models are built from real CT and MRI volumes with high detail, then anatomical accuracy is improved, but the model contains excessive irrelevant details and increases complexity
Solution Approach 1:
The patent extracts and removes irrelevant details from high-resolution medical images while preserving important anatomical structures. The statistical model retains only the most significant anatomical features needed for detection and tracking tasks, eliminating excessive detail that complicates the model without adding value.
Solution Approach 2:
The patent segments the heart into four distinct chambers (left atrium, left ventricle, right atrium, right ventricle) with clearly defined boundaries. This segmentation approach organizes the complex heart structure into manageable parts, each modeled with appropriate detail level, reducing overall model complexity while maintaining anatomical accuracy where needed.
2Measurement precision
If dense representation with many pseudo-landmarks is used for statistical shape modeling, then measurement precision is improved, but the optimization process becomes very slow and converges to local optima
Solution Approach 1:
The patent uses a sparse representation with a limited number of strategically selected landmarks instead of dense pseudo-landmarks. This partial action approach focuses computational effort on the most informative points for defining heart chamber geometry, achieving sufficient measurement precision while dramatically reducing optimization complexity and computation time.
Solution Approach 2:
The patent changes the parameter representation from dense pseudo-landmark coordinates to a smaller set of meaningful anatomical landmarks with explicit correspondence relationships. This parameter transformation simplifies the optimization landscape, enabling faster convergence to global optima while maintaining the precision needed for accurate heart modeling.
3Measurement precision
If manual labeling of correspondence in 3D is performed, then point correspondence accuracy is improved, but the process becomes difficult and time-consuming
Solution Approach 1:
The patent implements self-service through automatic establishment of point correspondence using the statistical model framework. The system automatically identifies corresponding landmarks across different heart models based on their anatomical definitions and spatial relationships, eliminating the need for manual labeling while maintaining high correspondence accuracy.
Solution Approach 2:
The patent performs preliminary action by pre-defining the correspondence relationships between landmarks in the statistical model before actual heart modeling begins. The landmark definitions and their correspondence rules are established in advance, allowing rapid automated matching without time-consuming manual intervention for each new heart model.
4Loss of information
If closed surface models are used for heart chambers, then completeness of representation is improved, but the ability to explicitly model valves and cusp points is reduced
Solution Approach 1:
The patent segments the heart chamber surfaces to create open models with explicitly defined boundaries at valve locations. By dividing the surface representation and leaving openings at valve positions, the model simultaneously maintains completeness of chamber representation and enables precise modeling of valves and cusp points as distinct anatomical features.
Solution Approach 2:
The patent uses valve annuli and cusp points as intermediary elements that connect different parts of the heart model. These intermediary structures serve as explicit markers for valve locations and orientations, enabling accurate representation of valve anatomy while maintaining the overall completeness of the chamber surface models.
Data Source
AI summary
A method and system for building a statistical four-chamber heart model from 3D volumes is disclosed. In order to generate the four-chamber heart model, each chamber is modeled using an open mesh, with holes at the valves. Based on the image data in one or more 3D volumes, meshes are generated and edited for the left ventricle (LV), left atrium (LA), right ventricle (RV), and right atrium (RA). Resampling to enforce point correspondence is performed during mesh editing. Important anatomic landmarks in the heart are explicitly represented in the four-chamber heart model of the present invention.