ArticleMedical physics2013
Tight-frame based iterative image reconstruction for spectral breast CT.
Article in Medical physics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advanced applications in chronic disease monitoring using IoT mobile sensing device data, machine learning algorithms and frame theory: a systematic review.Frontiers in public health · 2025Pooled it
- 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
- Beam angle optimization for proton therapy via group-sparsity based angle generation method.Medical physics · 2023Article
- Low-dose spectral reconstruction with global, local, and nonlocal priors based on subspace decomposition.Quantitative imaging in medicine and surgery · 2023Article
- Image-domain Material Decomposition for Spectral CT using a Generalized Dictionary Learning.IEEE transactions on radiation and plasma medical sciences · 2021Article
- Refined Locally Linear Transform-Based Spectral-Domain Gradient Sparsity and Its Applications in Spectral CT Reconstruction.IEEE access : practical innovations, open solutions · 2021Article
- 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
- Simultaneously spatial and temporal Higher-Order Total Variations for noise suppression and motion reduction in DCE and IVIM.Proceedings of SPIE--the International Society for Optical Engineering · 2020Article
- Block matching frame based material reconstruction for spectral CT.Physics in medicine and biology · 2019Article
- Non-Local Low-Rank Cube-Based Tensor Factorization for Spectral CT Reconstruction.IEEE transactions on medical imaging · 2019Article
- Low-dose spectral CT reconstruction using image gradientApplied mathematical modelling · 2018Article
- 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
- Evaluation of an Analytic Reconstruction Method as a Platform for Spectral Cone-beam CT.IEEE access : practical innovations, open solutions · 2018Article
- Tensor-Based Dictionary Learning for Spectral CT Reconstruction.IEEE transactions on medical imaging · 2017Article
- Frame-Based CT Image Reconstruction via the Balanced Approach.Journal of healthcare engineering · 2017Article
- TICMR: Total Image Constrained Material Reconstruction via Nonlocal Total Variation Regularization for Spectral CT.IEEE transactions on medical imaging · 2016Article
- 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
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
purposeTo investigate tight-frame based iterative reconstruction (TFIR) technique for spectral breast computed tomography (CT) using fewer projections while achieving greater image quality.
methodsThe experimental data were acquired with a fan-beam breast CT system based on a cadmium zinc telluride photon-counting detector. The images were reconstructed with a varying number of projections using the TFIR and filtered backprojection (FBP) techniques. The image quality between these two techniques was evaluated. The image's spatial resolution was evaluated using a high-resolution phantom, and the contrast to noise ratio (CNR) was evaluated using a postmortem breast sample. The postmortem breast samples were decomposed into water, lipid, and protein contents based on images reconstructed from TFIR with 204 projections and FBP with 614 projections. The volumetric fractions of water, lipid, and protein from the image-based measurements in both TFIR and FBP were compared to the chemical analysis.
resultsThe spatial resolution and CNR were comparable for the images reconstructed by TFIR with 204 projections and FBP with 614 projections. Both reconstruction techniques provided accurate quantification of water, lipid, and protein composition of the breast tissue when compared with data from the reference standard chemical analysis.
conclusionsAccurate breast tissue decomposition can be done with three fold fewer projection images by the TFIR technique without any reduction in image spatial resolution and CNR. This can result in a two-third reduction of the patient dose in a multislit and multislice spiral CT system in addition to the reduced scanning time in this system.
Indexed as
Identifiers
What OpenQuestion holds
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.