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SONAR: A Structure-Consistent Neural Operator for Null-Space-Aware Sparse View CT Reconstruction

arXiv · AI, language, vision and robotics · article · Sep 12, 2026 · UTC

Sparse-view computed tomography (CT) reduces radiation dose and acquisition time but remains severely ill-posed because incomplete projections poorly constrain null-space information. Existing learning-based methods often estimate this information in high-dimensional image space, conflate physical measurement errors with prediction errors, and depend on fixed discretizations. We propose SONAR, a Structure-Consistent Neural Operator for Null-Space-Aware Reconstruction. Instead of recovering the full null-space component, SONAR predicts a low-dimensional null-space-aware representation from the

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First collected: 2026-09-20T16:41:15.630Z. This is not the publication date.