CT Reconstruction

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 67 papers with code (235 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Learned Primal-dual Reconstruction
  20 Jul 2017 4 repositories listed
  We propose the Learned Primal-Dual algorithm for tomographic reconstruction.
• An Educated Warm Start For Deep Image Prior-Based Micro CT Reconstruction
  23 Nov 2021 3 repositories listed Syntology ran 5 of 5 samples · 0 unverified · 5 pointer-only (licence)
  Deep image prior (DIP) was recently introduced as an effective unsupervised approach for image restoration tasks.
• Framing U-Net via Deep Convolutional Framelets: Application to Sparse-view CT
  28 Aug 2017 3 repositories listed
  X-ray computed tomography (CT) using sparse projection views is a recent approach to reduce the radiation dose.
• X²-Gaussian: 4D Radiative Gaussian Splatting for Continuous-time Tomographic Reconstruction
  27 Mar 2025 2 repositories listed
  By unifying continuous motion modeling with hardware-free period learning, X²-Gaussian advances high-fidelity 4D CT reconstruction for dynamic clinical imaging.
• X-Field: A Physically Grounded Representation for 3D X-ray Reconstruction
  11 Mar 2025 2 repositories listed
  X-ray imaging is indispensable in medical diagnostics, yet its use is tightly regulated due to potential health risks.
• Radiative Gaussian Splatting for Efficient X-ray Novel View Synthesis
  7 Mar 2024 2 repositories listed Syntology ran 6 of 8 samples · 2 unverified · 8 pointer-only (licence)
  X-ray is widely applied for transmission imaging due to its stronger penetration than natural light.
• Structure-Aware Sparse-View X-ray 3D Reconstruction
  18 Nov 2023 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we propose a framework, Structure-Aware X-ray Neural Radiodensity Fields (SAX-NeRF), for sparse-view X-ray 3D reconstruction.
• Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems
  10 Mar 2023 2 repositories listed Syntology ran 16 of 27 samples · 11 unverified · 27 pointer-only (licence)
  In this study, we propose a novel and efficient diffusion sampling strategy that synergistically combines the diffusion sampling and Krylov subspace methods.
• One Sample Diffusion Model in Projection Domain for Low-Dose CT Imaging
  7 Dec 2022 2 repositories listed
  Therefore, we propose a fully unsupervised one sample diffusion model (OSDM)in projection domain for low-dose CT reconstruction.
• PYRO-NN: Python Reconstruction Operators in Neural Networks
  30 Apr 2019 2 repositories listed
  The high level Python API allows a simple use of the layers as known from Tensorflow.
• Wavelet Domain Residual Network (WavResNet) for Low-Dose X-ray CT Reconstruction
  4 Mar 2017 2 repositories listed
  Model based iterative reconstruction (MBIR) algorithms for low-dose X-ray CT are computationally complex because of the repeated use of the forward and backward projection.
• X-GRM: Large Gaussian Reconstruction Model for Sparse-view X-rays to Computed Tomography
  21 May 2025 1 repository listed
  Existing CT reconstruction works are limited to small-capacity model architecture and inflexible volume representation.
• TomoSelfDEQ: Self-Supervised Deep Equilibrium Learning for Sparse-Angle CT Reconstruction
  28 Feb 2025 1 repository listed
  Deep learning has emerged as a powerful tool for solving inverse problems in imaging, including computed tomography (CT).
• Unsupervised Self-Prior Embedding Neural Representation for Iterative Sparse-View CT Reconstruction
  8 Feb 2025 1 repository listed
  Emerging unsupervised implicit neural representation (INR) methods, such as NeRP, NeAT, and SCOPE, have shown great potential to address sparse-view computed tomography (SVCT) inverse problems.
• Learning Difference-of-Convex Regularizers for Inverse Problems: A Flexible Framework with Theoretical Guarantees
  1 Feb 2025 1 repository listed
  Furthermore, we provide theoretical insights into the conditions under which optimal regularizers can be expressed as DC functions.
• Bigger Isn't Always Better: Towards a General Prior for Medical Image Reconstruction
  13 Jan 2025 1 repository listed
  Diffusion model have been successfully applied to many inverse problems, including MRI and CT reconstruction.
• Hierarchical Decomposed Dual-domain Deep Learning for Sparse-View CT Reconstruction
  9 Jan 2025 1 repository listed
  Recently, deep learning strategies employing image-domain networks have demonstrated remarkable performance in eliminating the streaking artifact caused by analytic reconstruction methods with sparse projection views.
• Regression Conformal Prediction under Bias
  7 Oct 2024 1 repository listed
  Specifically for absolute residual and quantile-based non-conformity scores, we prove: 1) the upper bound of symmetrically adjusted interval lengths increases by 2|b| where b is a globally applied scalar value…
• RN-SDEs: Limited-Angle CT Reconstruction with Residual Null-Space Diffusion Stochastic Differential Equations
  20 Sep 2024 1 repository listed
  Computed tomography is a widely used imaging modality with applications ranging from medical imaging to material analysis.
• DIFR3CT: Latent Diffusion for Probabilistic 3D CT Reconstruction from Few Planar X-Rays
  27 Aug 2024 1 repository listed
  Computed Tomography (CT) scans are the standard-of-care for the visualization and diagnosis of many clinical ailments, and are needed for the treatment planning of external beam radiotherapy.
• X-Recon: Learning-based Patient-specific High-Resolution CT Reconstruction from Orthogonal X-Ray Images
  22 Jul 2024 1 repository listed
  Rapid and accurate diagnosis of pneumothorax, utilizing chest X-ray and computed tomography (CT), is crucial for assisted diagnosis.
• Learning 3D Gaussians for Extremely Sparse-View Cone-Beam CT Reconstruction
  1 Jul 2024 1 repository listed
  Cone-Beam Computed Tomography (CBCT) is an indispensable technique in medical imaging, yet the associated radiation exposure raises concerns in clinical practice.
• XctDiff: Reconstruction of CT Images with Consistent Anatomical Structures from a Single Radiographic Projection Image
  7 Jun 2024 1 repository listed
  In this paper, we present XctDiff, an algorithm framework for reconstructing CT from a single radiograph, which decomposes the reconstruction process into two easily controllable tasks: feature extraction and CT…
• Learning Image Priors through Patch-based Diffusion Models for Solving Inverse Problems
  4 Jun 2024 1 repository listed
  This paper proposes a method to learn an efficient data prior for the entire image by training diffusion models only on patches of images.
• MVMS-RCN: A Dual-Domain Unfolding CT Reconstruction with Multi-sparse-view and Multi-scale Refinement-correction
  27 May 2024 1 repository listed
  We propose a novel dual-domain deep unfolding unified framework that offers a great deal of flexibility for multi-sparse-view CT reconstruction with different sampling views through a single model.
• EAGLE: An Edge-Aware Gradient Localization Enhanced Loss for CT Image Reconstruction
  15 Mar 2024 1 repository listed
  However, the choice of loss function profoundly affects the reconstructed images.
• Low-Dose CT Reconstruction Using Dataset-free Learning
  17 Feb 2024 1 repository listed
  Although supervised-deep-learning-based reconstruction methods have demonstrated superior performance compared to conventional model-driven reconstruction algorithms, they require collecting massive pairs of low-dose…
• Enhancing signal detectability in learning-based CT reconstruction with a model observer inspired loss function
  15 Feb 2024 1 repository listed Syntology ran 6 of 10 samples · 4 unverified
  Deep neural networks used for reconstructing sparse-view CT data are typically trained by minimizing a pixel-wise mean-squared error or similar loss function over a set of training images.
• Estimating Epistemic and Aleatoric Uncertainty with a Single Model
  5 Feb 2024 1 repository listed Syntology ran 3 of 5 samples · 2 unverified · 5 pointer-only (licence)
  Estimating and disentangling epistemic uncertainty, uncertainty that is reducible with more training data, and aleatoric uncertainty, uncertainty that is inherent to the task at hand, is critically important when…
• Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series
  29 Jan 2024 1 repository listed
  In this study, we introduce a Fourier series-based trainable filter for computed tomography (CT) reconstruction within the filtered backprojection (FBP) framework.

Syntology lines on 6 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.