Voxel Build 3D Mesh Generation from 2D Images
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Solution Overview
Problem
Current systems require a time-consuming and repetitive process to generate three-dimensional images from two-dimensional data, limiting efficient evaluation and manipulation of image densities and abnormalities in three-dimensional space.
Innovation Solution
A method that uses a mesh generating program to create a three-dimensional mesh from two-dimensional images based on user-defined threshold values, allowing for the evaluation and mapping of pixels into three-dimensional voxels, enabling manipulation of these voxels as a single mesh for enhanced visualization and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methods are used to generate three-dimensional images from two-dimensional data, then the process can be completed, but it requires a time-consuming and repetitive process
Solution Approach 1:
The system pre-processes two-dimensional images by evaluating every pixel against user-defined threshold values and flagging pixels that meet the criteria. This preliminary action of threshold evaluation and pixel flagging enables rapid three-dimensional mesh generation without requiring time-consuming repetitive processing, thus resolving the contradiction between completion and processing time.
Solution Approach 2:
The invention creates a three-dimensional mesh by copying and mapping flagged pixels from two-dimensional images into three-dimensional voxel space. This copying process efficiently transforms pre-processed two-dimensional data into three-dimensional representations, significantly reducing the time required compared to traditional methods of generating three-dimensional images from scratch.
2Ease of operation
If traditional methods are used to create three-dimensional images, then the process can be completed, but it is a repetitive process that limits efficient evaluation
Solution Approach 1:
The system segments the three-dimensional space into discrete voxels corresponding to flagged pixels in the two-dimensional images. This segmentation allows for efficient evaluation and manipulation of individual voxels as separate entities while maintaining the overall three-dimensional structure, thereby improving ease of operation without excessive complexity.
Solution Approach 2:
The invention transitions from two-dimensional image data to three-dimensional voxel representations, adding the third dimension of spatial depth. This dimensional change enables users to evaluate and manipulate data in three-dimensional space, improving evaluation efficiency while the systematic mapping process keeps the complexity manageable.
3Adaptability or versatility
If users load two-dimensional images into a three-dimensional mesh generating program, then three-dimensional visualization is achieved, but the process requires specific threshold value inputs
Solution Approach 1:
The system allows users to dynamically adjust threshold values according to their specific evaluation needs. The threshold values can be modified during the process, enabling adaptability to different imaging scenarios and data types. This dynamic adjustment capability maintains versatility while the automated processing keeps the overall process simple and user-friendly.
Data Source
AI summary
A computer-implemented method that allows users evaluate the densities of images and search for abnormalities in three-dimensional space. The voxel buildup uses a series of two-dimensional images and evaluates every pixel based on the user described predetermined threshold value at runtime. Once all the voxels are created, the user may manipulate the set of voxels as if they are one mesh.