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经典与迭代重建

经典 CT 重建是指利用解析反演公式或迭代优化,从线积分投影中恢复图像,不含学习得到的组件。解析方法,即用于平行束和扇束的滤波反投影(FBP)以及用于锥束的 Feldkamp-Davis-Kress(FDK)算法,直接反演 Radon 变换;由于速度快、行为可预测,它们仍是大多数扫描仪的默认方法。

迭代方法把重建看作求解一个大型线性方程组或优化问题。代数方法(ART、SART、SIRT)、统计方法(最大似然、惩罚似然、基于模型的迭代重建)以及 CGLS 等 Krylov 求解器,会显式地建模扫描仪和噪声,在数据含噪或不完整时优势明显。

正则化让迭代方法能在数据很少时依然奏效:全变分(TV)及其推广、小波与剪切波稀疏、字典学习和非局部惩罚项。压缩感知在 2006 年前后为此提供了理论基础,而这些求解器至今仍是许多深度学习方法中负责数据一致性的骨架。

在可检索的目录中浏览全部 71 篇「经典与迭代重建」论文

入门推荐

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论文

共 71 篇,按时间倒序列出最新的 30 篇。

论文发表出处年份链接
Complex Wavelet-Based Sinogram Segmentation for Metal Artifact Reduction in Cone-Beam CTPMB2026paper
Computed Tomography Reconstruction Algorithm Using Markov Random Field ModelJ. Phys. Soc. Jpn.2026paper
Cross-Distribution Diffusion Priors-Driven Iterative Reconstruction for Sparse-View CTTMI2026paper
Plug-and-Play Diffusion Meets ADMM: Dual-Variable Coupling for Robust Medical Image ReconstructionICML2026paper · code · project
Deep Pseudo-Proximal Map: A Self-Supervised Data-Fitting Agent for Iterative Reconstruction预印本2026paper
H3D-MarNet: Wavelet-Guided Dual-Path Learning for Metal Artifact Suppression and CT Modality Transformation for Radiotherapy WorkflowsICPR2026paper
Model-Based Iterative Reconstruction with View-Dependent Detector Displacements for Cone-Beam CT预印本2026paper
Radon Transforms of Projection Functions and Aleksandrov-Fenchel Inequalities预印本2026paper
Robustness and Stability Analysis of Differentiable Shift-Variant FBP for Cone-Beam CT under Challenging Acquisition SettingsMELBA2026paper · project
Variational Garrote for Sparse Inverse ProblemsJ. Comput. Sci.2026paper
An Iterative Reconstruction Method for Dental Cone-Beam Computed Tomography with a Truncated Field of View预印本2025paper
Learning Cocoercive Conservative Denoisers via Helmholtz Decomposition for Poisson Inverse ProblemsNeurIPS2025paper · code
Learning Wavelet-Sparse FDK for 3D Cone-Beam CT ReconstructionFully3D2025paper
MONSTR: Model-Oriented Neutron Strain Tomographic ReconstructionICIP2025paper
System-Embedded Diffusion Bridge ModelsNeurIPS2025paper · code
Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier Series预印本2024paper
How auto-differentiation can improve CT workflows: classical algorithms in a modern frameworkOpt. Express2024paper
Iterative reconstruction of low-dose CT based on differential sparseBSPC2023paper
Iterative Reconstruction for Low-Dose CT using Deep Gradient Priors of Generative ModelTRPMS2022paper · code
Adversarially learned iterative reconstruction for imaging inverse problemsSSVM2021paper · code
Accurate and robust sparse-view angle CT image reconstruction using deep learning and prior image constrained compressed sensing (DL-PICCS)Med Phys2021paper
FISTA-Net: Learning a Fast Iterative Shrinkage Thresholding Network for Inverse Problems in ImagingTMI2021paper · code
Limited-Angle CT Reconstruction via the L1/L2 MinimizationSIAM J. Imaging Sci.2021paper
Learning to Reconstruct CT Images From the VVBP-TensorTMI2021paper
FSTensor: Full-spectrum-knowledge-aware tensor model for energy-resolved CT iterative reconstructionTMI2020paper
Radon Inversion via Deep LearningTMI2020paper
Learned convex regularizers for inverse problems预印本2020paper
Momentum-Net: Fast and convergent iterative neural network for inverse problemsTPAMI2020paper
Moreau-envelope-enhanced nonlocal shearlet transform and total variation for sparse-view CT reconstructionMeas. Sci. Technol.2020paper
Image Reconstruction: From Sparsity to Data-Adaptive Methods and Machine LearningProc. IEEE2020paper

在可检索的目录中浏览全部 71 篇「经典与迭代重建」论文

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