PRISM-NAF: Physically Realistic Intensity-Domain Spectral Modeling of Neural Attenuation Fields for Sparse-View CBCT Reconstruction

Neural attenuation fields (NAF) provide a data-efficient approach to sparse-view cone-beam CT (CBCT) reconstruction, yet most methods retain a simplified detector model: each pixel is represented by a single center ray, while spectral and low-frequency detector effects are modeled with weakly constrained spatial degrees of freedom. Under sparse views, these mismatches can be absorbed into the reconstructed attenuation field, yielding visually plausible but systematically distorted anatomy. We propose Physically Realistic Intensity-Domain Spectral Modeling of NAF (PRISM-NAF), a detector-aware neural attenuation field that structures these degrees of freedom at the measurement level. Coherent Aperture Aggregation samples multiple physically realizable paths over each area-based detector pixel; Material-Coupled Response replaces a free voxel-wise beam-hardening spread with a compact, globally shared monotone function of attenuation; and a coarse non-negative detector-plane intensity field provides a low-bandwidth correction at the stage where additive photon flux enters the measurement. We interpret the latter as an effective nuisance correction rather than a calibrated scatter estimate. Experiments on two real anthropomorphic phantom datasets spanning three anatomies and multiple sparse-view settings show that PRISM-NAF improves perceptual reconstruction quality and vascular-structure fidelity over state-of-the-art methods, while reducing structured artifacts and preserving fine anatomical boundaries.