ArticlePhysics in medicine and biology2012
Dual-dictionary learning-based iterative image reconstruction for spectral computed tomography application.
Article in Physics in medicine and biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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24 citing papers in PubMed, 69 citations in OpenAlex.
- ZS4D: Zero-Shot Self-Similarity-Steered Denoiser for Volumetric Photon-Counting CT.IEEE transactions on radiation and plasma medical sciences · 2026Article
- Enhancing photon-counting computed tomography reconstruction via subspace dictionary learning and spatial sparsity regularization.Quantitative imaging in medicine and surgery · 2025Article
- Learned Tensor Neural Network Texture Prior for Photon-Counting CT Reconstruction.IEEE transactions on medical imaging · 2024Article
- Machine Learned Texture Prior From Full-Dose CT Database via Multi-Modality Feature Selection for Bayesian Reconstruction of Low-Dose CT.IEEE transactions on medical imaging · 2023Article
- Image-spectral decomposition extended-learning assisted by sparsity for multi-energy computed tomography reconstruction.Quantitative imaging in medicine and surgery · 2023Article
- Spectral CT Reconstruction via Low-Rank Representation and Region-Specific Texture Preserving Markov Random Field Regularization.IEEE transactions on medical imaging · 2020Article
- Multi-energy CT reconstruction using tensor nonlocal similarity and spatial sparsity regularization.Quantitative imaging in medicine and surgery · 2020Article
- DECT-MULTRA: Dual-Energy CT Image Decomposition With Learned Mixed Material Models and Efficient Clustering.IEEE transactions on medical imaging · 2020Article
- The evolution of image reconstruction for CT-from filtered back projection to artificial intelligence.European radiology · 2019Review
- Non-Local Low-Rank Cube-Based Tensor Factorization for Spectral CT Reconstruction.IEEE transactions on medical imaging · 2019Article
- Spatial-Spectral Cube Matching Frame for Spectral CT Reconstruction.Inverse problems · 2018Article
- Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction.Inverse problems · 2018Article
- Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI.IEEE transactions on bio-medical engineering · 2017Article
- Tensor-Based Dictionary Learning for Spectral CT Reconstruction.IEEE transactions on medical imaging · 2017Article
- TICMR: Total Image Constrained Material Reconstruction via Nonlocal Total Variation Regularization for Spectral CT.IEEE transactions on medical imaging · 2016Article
- A framelet-based iterative maximum-likelihood reconstruction algorithm for spectral CT.Inverse problems · 2016Article
- Patch-based models and algorithms for image processing: a review of the basic principles and methods, and their application in computed tomography.International journal of computer assisted radiology and surgery · 2016Review
- Dictionary learning for data recovery in positron emission tomography.Physics in medicine and biology · 2015Article
- Recent Development of Dual-Dictionary Learning Approach in Medical Image Analysis and Reconstruction.Computational and mathematical methods in medicine · 2015Review
- A high-resolution photon-counting breast CT system with tensor-framelet based iterative image reconstruction for radiation dose reduction.Physics in medicine and biology · 2014Article
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
In this study, we investigated the effectiveness of a novel iterative reconstruction (IR) method coupled with dual-dictionary learning (DDL) for image reconstruction in a dedicated breast computed tomography (CT) system based on a cadmium-zinc-telluride (CZT) photon-counting detector and compared it to the filtered-back-projection (FBP) method with the ultimate goal of reducing the number of projections necessary for reconstruction without sacrificing the image quality. Postmortem breast samples were scanned in a fan-beam CT system and were reconstructed from 100 to 600 projections with both IR and FBP methods. The contrast-to-noise ratio (CNR) between the glandular and adipose tissues of the postmortem breast samples was calculated to compare the quality of images reconstructed from IR and FBP. The spatial resolution of the two reconstruction techniques was evaluated using aluminum (Al) wires with diameters of 643, 813, 1020, 1290 and 1630 µm in a plastic epoxy resin phantom with a diameter of 13 cm. Both the spatial resolution and the CNR were improved with IR compared to FBP for the images reconstructed from the same number of projections. In comparison with FBP reconstruction, the CNR was improved from 3.4 to 7.5 by using the IR method with six-fold fewer projections while maintaining the same spatial resolution. The study demonstrated that the IR method coupled with DDL could significantly reduce the required number of projections for a CT reconstruction compared to the FBP method while achieving a much better CNR and maintaining the same spatial resolution. From this, the radiation dose and scanning time can potentially be reduced by a factor of approximately 6 by using this IR method for image reconstruction in a CZT-based breast CT system.
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