Gaussian Material Fields for Volumetric Multi-Energy CT Decomposition

Key points

• We observe that spatial primitives can be shared across materials without tying their coefficients, but their local capacity must respond to material-specific reconstruction needs.1
• We introduce Gaussian material fields, which represent multiple material distributions with shared anisotropic 3D Gaussian primitives and independent nonnegative material coefficients.1
• To reconstruct this representation from multi-energy projections, a differentiable spectral forward model combines Gaussian material path integrals with a calibrated basis matrix, enabling joint optimization of spatial geometry and material composition.1
• These results establish Gaussian material fields as an explicit, adaptive representation for volumetric multi-material reconstruction.1

Sources (1)

• [1]Gaussian Material Fields for Volumetric Multi-Energy CT Decomposition
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 05:47 AM

  Volumetric material decomposition in multi-energy computed tomography requires a representation that organizes multiple three-dimensional material fields in a common spatial domain while retaining differences in composition and local structure.

  We observe that spatial primitives can be shared across materials without tying their coefficients, but their local capacity must respond to material-specific reconstruction needs.

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