Hugging Face Trending Papers

Splat-based Metal Artifact Reduction in Cone-Beam CT via Polychromatic Modeling

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Cone-beam computed tomography (CBCT) enables volumetric reconstruction from X-ray projections, but suffers from severe artifacts--especially beam hardening--when imaging materials with high attenuation such as metals. These artifacts arise from the polychromatic nature of X-rays and are not properly addressed by conventional monochromatic reconstruction algorithms.

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arXiv Computer Vision
Aug 25

Toward a Foundation Plug-and-Play Prior for Computed Tomography Reconstruction via a Multimodal Diffusion Model

The paper proposes a single diffusion model trained across multiple imaging domains to act as a reusable prior for computed tomography (CT) reconstruction. By keeping the model frozen, it is applied to three distinct datasets—flaw analysis in additively manufactured metal parts using cone‑beam X‑ray CT, and concrete microstructure imaging with parallel‑beam neutron CT—each differing in modality, geometry, material, and degradation. In all cases, the method outperforms analytic reconstructions, demonstrating its potential as a foundation plug‑and‑play prior for heterogeneous CT problems.

By Haley Duba-Sullivan, Patxi Fernandez-Zelaia, Obaidullah Rahman, Amirkoushyar Ziabari
arXiv AI
Jul 15

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data

arXiv:2607. 12175v1 Announce Type: cross Abstract: X-ray tomography enables nondestructive characterization of material microstructures, while advances in micro-CT imaging have accelerated volumetric data acquisition and reconstruction.

By Pradyumna Elavarthi, Arun J. Bhattacharjee, Harrison Lisabeth, Anca Ralescu, Petrus H. Zwart, Dilworth Parkinson, Elizabeth G. Clark
arXiv Computer Vision
2d ago

VoxelSynth3D: Interpretable Volumetric Image-Domain Metal Artifact Reduction with a Paired Synthetic CLINIC-Metal Benchmark

VoxelSynth3D is a training‑free 3D image‑domain framework that reduces metal artifacts in postoperative musculoskeletal CT by combining support masking, normalized tissue synthesis, deviation gating, and restricted edge refinement. The method preserves implant voxels while correcting surrounding tissue artifacts and was evaluated on a newly constructed Synthetic CLINIC‑Metal benchmark, showing a reduction in RMSE from 801.48 to 786.18 HU on 40 held‑out cases. Compared to a 3D Gaussian smoother, VoxelSynth3D achieved a 13.58 HU improvement and maintained clean-edge agreement beyond 5 mm from metal.

By Amritesh Banerjee, Abdul Basit, Renil Renji Joseph, Nouhaila Innan, Muhammad Shafique
arXiv Computer Vision
Sep 25

SpectralCTGaussians: Projection-Domain Reconstruction and Basis Material Decomposition for Spectral CT using 3D Gaussian Splatting

SpectralCTGaussians introduces a novel spectral CT reconstruction and basis material decomposition technique that employs 3D Gaussian splatting with per‑Gaussian material fractions and energy‑dependent basis functions. By jointly optimizing these parameters across all energy channels via a differentiable polychromatic forward model, the method achieves superior novel view synthesis and higher PSNR for spectral CT volume reconstruction compared to traditional and learning‑based baselines. It also provides one‑step material decomposition with direct RGB segmentation and recovers the photoelectric basis more accurately than existing pipelines.

By Reinout Vos, Saptarshi Neil Sinha, Michael Weinmann