AI RESEARCH
Novel 3D Binary Indexed Tree for Volume Computation of 3D Reconstructed Models from Volumetric Data
arXiv CS.CV
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ArXi:2412.10441v2 Announce Type: replace-cross In the burgeoning field of medical imaging, precise computation of 3D volume holds a significant importance for subsequent qualitative analysis of 3D reconstructed objects. Combining multivariate calculus, marching cube algorithm, and binary indexed tree data structure, we developed an algorithm for efficient computation of intrinsic volume of any volumetric data recovered from computed tomography (CT) or magnetic resonance (MR). We proposed the 30 configurations of volume values based on the polygonal mesh generation method.