ArticleSIAM journal on imaging sciences2018
MULTI-ENERGY CONE-BEAM CT RECONSTRUCTION WITH A SPATIAL SPECTRAL NONLOCAL MEANS ALGORITHM.
Article in SIAM journal on imaging sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Simultaneous Image Reconstruction and Element Decomposition for Iodine Contrast Agent Visualization in Multienergy Element-Resolved Cone Beam CT.Frontiers in oncology · 2022Article
- A prior image constraint robust principal component analysis reconstruction method for sparse segmental multi-energy computed tomography.Quantitative imaging in medicine and surgery · 2021Article
- Comparison of three undersampling approaches in computed tomography reconstruction.Quantitative imaging in medicine and surgery · 2019Article
- Non-Local Low-Rank Cube-Based Tensor Factorization for Spectral CT Reconstruction.IEEE transactions on medical imaging · 2019Article
- Multienergy element-resolved cone beam CT (MEER-CBCT) realized on a conventional CBCT platform.Medical physics · 2018Article
- Signal-to-noise ratio analysis and improvement for fluorescence tomography imaging.The Review of scientific instruments · 2018Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Multi-energy computed tomography (CT) is an emerging medical image modality with a number of potential applications in diagnosis and therapy. However, high system cost and technical barriers obstruct its step into routine clinical practice. In this study, we propose a framework to realize multi-energy cone beam CT (ME-CBCT) on the CBCT system that is widely available and has been routinely used for radiotherapy image guidance. In our method, a kVp switching technique is realized, which acquires x-ray projections with kVp levels cycling through a number of values. For this kVp-switching based ME-CBCT acquisition, x-ray projections of each energy channel are only a subset of all the acquired projections. This leads to an undersampling issue, posing challenges to the reconstruction problem. We propose a spatial spectral non-local means (ssNLM) method to reconstruct ME-CBCT, which employs image correlations along both spatial and spectral directions to suppress noisy and streak artifacts. To address the intensity scale difference at different energy channels, a histogram matching method is incorporated. Our method is different from conventionally used NLM methods in that spectral dimension is included, which helps to effectively remove streak artifacts appearing at different directions in images with different energy channels. Convergence analysis of our algorithm is provided. A comprehensive set of simulation and real experimental studies demonstrate feasibility of our ME-CBCT scheme and the capability of achieving superior image quality compared to conventional filtered backprojection-type (FBP) and NLM reconstruction methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.