Multi-Surface Modeling for Anatomical Structures
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Solution Overview
Problem
Current surface modeling techniques are insufficient for accurately representing complex anatomical structures like the heart, which require modeling both cavities and muscle surfaces that interdepend on each other, necessitating an improved method for constructing multi-surface models from multi-dimensional datasets.
Innovation Solution
The method involves constructing adaptive first and second surface meshes corresponding to different parts of the object, combining them using binary operations such as union, intersection, and difference to form a multi-surface model, which can be refined or coarsened to achieve the desired granularity, and optionally performed interactively or in batch mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional single-surface modeling techniques are used, then the modeling process is simple, but the accuracy of representing complex anatomical structures is insufficient
Solution Approach 1:
The patent divides the complex anatomical structure into multiple independent surface meshes, each representing a specific anatomical component (e.g., endocardium, epicardium, myocardium). These segmented surfaces can be modeled and processed independently, then combined to form the complete multi-surface model, thereby improving modeling accuracy while maintaining manageable complexity
Solution Approach 2:
The patent combines multiple adaptive surface meshes representing different anatomical structures into a unified multi-surface model. This merging process integrates the detailed geometries of individual surfaces (cavities, muscle layers, vessels) to create a comprehensive representation that accurately captures the complex spatial relationships and interdependencies of anatomical structures
2Manufacturing precision
If detailed adaptive surface meshes are constructed for each part, then the anatomical representation is more accurate, but the computational resources and processing time increase
Solution Approach 1:
By segmenting the anatomical model into separate adaptive surface meshes for different structures, the patent enables parallel processing of each surface independently. This segmentation allows computational resources to be distributed across multiple surfaces simultaneously, reducing overall processing time while maintaining high accuracy for each anatomical component
Solution Approach 2:
The patent performs preliminary construction of individual adaptive surface meshes for each anatomical part before combining them. This preliminary action allows each surface to be optimized and processed separately using appropriate algorithms, and the results are then integrated, thereby reducing the total computational burden compared to processing the entire complex structure as a single unit
3Adaptability or versatility
If multiple independent surface meshes are combined, then the multi-surface model can represent complex structures, but the model complexity increases
Solution Approach 1:
The patent segments the complex anatomical structure into distinct surface meshes, each representing a specific anatomical component with its own topological and geometric properties. This segmentation allows the model to capture the unique characteristics of each structure (cavities, muscle layers, vessels) while maintaining manageable complexity through modular organization
Solution Approach 2:
The patent merges multiple adaptive surface meshes into a unified multi-surface model that preserves the individual characteristics of each component while establishing their spatial relationships. This merging creates a versatile model capable of representing complex anatomical structures and their interdependencies, with the added benefit that the modular structure allows for selective processing and analysis of specific components
Data Source
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AI summary
Modelling of organ surfaces is a well-established method that may serve in computer-supported teaching, but also in image-based medical diagnosis and in clinical interventions. According to an exemplary embodiment of the present invention, a method of constructing a multi-surface model from a multi-dimensional dataset of an object of interest is provided, which combines single basic two-dimensional manifold surface meshes, resulting in a multi-surface model. According to an aspect of the present invention, this resulting model may be a non-two-dimensional manifold mesh.