Algorithm for Efficient 3D Volume Computation from CT and MR Data
An innovative algorithm has been created that integrates multivariate calculus, the marching cube algorithm, and the binary indexed tree data structure to efficiently calculate intrinsic volume from volumetric data obtained through computed tomography (CT) or magnetic resonance (MR). This algorithm processes the data in scan-line order while simultaneously reconstructing it to form a Fenwick tree, which enhances query speed and aids users in modifying slicing or transforming models. It introduces 30 configurations of volume values derived from polygonal mesh generation. Accuracy evaluations conducted on both simple 3D shapes (such as spheres and cylinders) and intricate structures (like lungs and cardiac chambers) revealed a deviation of no more than ±0.004 cm³.
Key facts
- Algorithm combines multivariate calculus, marching cube algorithm, and binary indexed tree data structure.
- Processes data in scan-line order simultaneously with reconstruction to create a Fenwick tree.
- Proposes 30 configurations of volume values based on polygonal mesh generation.
- Tested on simple 3D objects (sphere, cylinder) and complex structures (lungs, cardiac chambers).
- Deviation within ±0.004 cm³.
- Designed for volumetric data from CT or MR.
- Aims for efficient volume computation and user editing of slicing or transforming models.
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