3D Anatomical Mesh Visualization With Scene Graph Interaction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing anatomical education systems fail to provide scalable, interactive learning experiences for larger groups, lack integration of actual patient imaging data, and are hindered by financial and accessibility barriers, preventing comprehensive understanding of anatomy.
Innovation Solution
A processor-implemented method and system for generating 3D meshes of volumetric in-vivo images by segmenting and voxel subdivision, constructing scene graphs, and enabling interactive visualization with real-time updates, incorporating additional data for contextualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional anatomical education methods (volumetric illustrations, tangible models, cadaver dissection) are used, then anatomical visualization is provided, but the 3D nature of human anatomy is inadequately represented and costs are high with ethical dilemmas
Solution Approach 1:
The patent creates digital 3D copies of anatomical structures from real patient imaging data (CT and MRI scans). These digital models serve as virtual replicas that eliminate the need for physical cadavers and expensive tangible models, providing accurate anatomical representation without ethical dilemmas or high costs.
Solution Approach 2:
The patent replaces physical mechanical systems (cadaver dissection, tangible models) with computational and digital systems. By using image processing algorithms and 3D rendering software, the system substitutes physical manipulation with digital visualization, achieving the same educational objectives without the drawbacks of traditional methods.
2Measurement precision
If online 3D anatomical atlases and virtual reality platforms are used, then anatomical visualization is enhanced, but scalable interactive learning for larger groups is not supported and actual patient imaging data is not incorporated
Solution Approach 1:
The patent creates a universal platform that can serve multiple functions: it works with different imaging modalities (CT, MRI), supports various levels of interaction (rotation, zooming, sectioning), and can be accessed by multiple users simultaneously through web browsers. This multi-functionality enables scalable educational deployment without sacrificing visualization quality.
Solution Approach 2:
The patent introduces a web-based intermediary layer that connects users to the 3D anatomical models. This intermediary enables remote access and simultaneous multi-user interaction without requiring expensive VR hardware, thus scaling the system to larger groups while maintaining high visualization quality through standardized web technologies.
3Measurement precision
If VR headsets and specific hardware are required, then anatomical visualization is provided, but financial and accessibility barriers prevent full integration into educational institutions
Solution Approach 1:
The patent replaces expensive, specialized VR hardware with accessible, low-cost web browsers that run on standard computers and mobile devices. This substitution dramatically reduces the financial barrier to entry, allowing widespread adoption in educational institutions without requiring significant infrastructure investment.
Solution Approach 2:
The patent creates a universal web-based platform that functions across multiple devices and operating systems without requiring specialized hardware. This cross-platform compatibility ensures accessibility for all users regardless of their device, eliminating the need for expensive VR headsets while maintaining anatomical visualization capabilities.
4Measurement precision
If existing systems are used, then some 3D visualization is provided, but concurrent presentation of 3D anatomical structures and their radiological counterparts is not achieved
Solution Approach 1:
The patent merges 3D anatomical models with their source radiological images (CT and MRI scans) into a unified visualization system. Users can simultaneously view the rendered 3D structure and the original 2D imaging data, maintaining the connection between the anatomical model and its radiological foundation for comprehensive educational value.
Data Source
AI summary
Embodiments herein provide a processor-implemented method for generating and visualizing three-dimensional (3D) meshes of volumetric in-vivo images of anatomical structures. The processor-implemented method begins by segmenting medical imaging data, derived from magnetic resonance imaging (MRI) and computed tomography (CT) scans, into fine structures using segmentation techniques. Subsequently, voxel subdivision methods are applied to generate 3D meshes, representing the geometric characteristics of the segmented structures. A scene graph is then constructed to capture the spatial relationships and attributes, such as geometry or texture, of the 3D meshes. The scene graph facilitates rendering the 3D meshes, enabling visualization of structural connections at the node level, where each node corresponds to a specific fine structure. The 3D visualization system is delivered to user devices, supports enhanced analysis and understanding of complex anatomical relationships, making it particularly valuable for medical and educational applications.