# TRACE: Two-Stage Detector-Response Estimation With Angular Cosine Expansion for Ring Artifact Correction in Photon-Counting CT

arXiv: https://arxiv.org/abs/2609.15834 · HTML: https://mlsanity.com/paper/2609.15834/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 42 references that are in the map.
- First posted on arXiv 14 Sep 2026.

## Builds on (most cited first, 4 of 4)

- [Ring Artifacts Removal Based on Implicit Neural Representation of Sinogram Data](https://mlsanity.com/paper/2409.15731/) (2024)
- [Ring artifacts correction in compressed sensing tomographic reconstruction](https://mlsanity.com/paper/1502.01480/) (2015)
- [Multi-stage Deep Learning Artifact Reduction for Pallel-beam Computed Tomography](https://mlsanity.com/paper/2309.00494/) (2023)
- [A Dual-domain Regularization Method for Ring Artifact Removal of X-ray CT](https://mlsanity.com/paper/2403.08247/) (2024)

## Abstract (arXiv)

Detector response nonuniformity introduces systematic projection errors and ring artifacts in photon-counting detector computed tomography (PCD-CT). In measured PCD-CT data, residual stripe amplitudes vary slowly with projection angle, which fixed-bias models cannot adequately capture. We propose TRACE, a two-stage unsupervised sinogram decomposition method for estimating and correcting these response-related errors. TRACE represents stripes as a fixed bias plus low-order discrete cosine transform (DCT) components, using a small number of coefficients to describe angular variations at each detector element. A learnable analysis--synthesis architecture represents the ideal projections, while two-stage optimization separates them from fixed and then dynamic stripes. An angular-gradient soft orthogonality constraint suppresses correlated variations within the shared DCT gradient subspace, reducing the leakage of object structures into the artifact estimate. All parameters are optimized directly on the measured sinogram without paired training data. Experiments on measured QRM mouse phantom and porcine trotter data show that TRACE suppresses ring artifacts and improves image uniformity while preserving edge sharpness, soft-tissue texture, and trabecular detail.