ArticleIEEE transactions on medical imaging2014
Cine cone beam CT reconstruction using low-rank matrix factorization: algorithm and a proof-of-principle study.
Article in IEEE transactions on medical imaging, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed.
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- A competition-proven deep learning-based dual-domain framework for low-dose CBCT reconstruction.Quantitative imaging in medicine and surgery · 2026Article
- Enhancing low-dose CT denoising via multi-view knowledge transfer without paired data.Frontiers in radiology · 2026Article
- A new hybrid model for enhancing low-dose CT images using EfficientNetV2 and WGAN-GP: a multi-loss approach.European journal of medical research · 2025Article
- Time-resolved dynamic CBCT reconstruction using prior-model-free spatiotemporal Gaussian representation (PMF-STGR).Physics in medicine and biology · 2025Article
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- Compressed radiotherapy treatment planning: A new paradigm for rapid and high-quality treatment planning optimization.Medical physics · 2025Article
- Multi-scale perceptual modulation network for low-dose computed tomography denoising.Quantitative imaging in medicine and surgery · 2024Article
- A review on 4D cone-beam CT (4D-CBCT) in radiation therapy: Technical advances and clinical applications.Medical physics · 2024Review
- Dynamic CBCT imaging using prior model-free spatiotemporal implicit neural representation (PMF-STINR).Physics in medicine and biology · 2024Article
- A two-stage deep-learning framework for CT denoising based on a clinically structure-unaligned paired data set.Quantitative imaging in medicine and surgery · 2024Article
- ProxNF: Neural Field Proximal Training for High-Resolution 4D Dynamic Image Reconstruction.IEEE transactions on computational imaging · 2024Article
- Low-dose CT reconstruction using dataset-free learning.PloS one · 2024Article
- Spatiotemporal image reconstruction to enable high-frame-rate dynamic photoacoustic tomography with rotating-gantry volumetric imagers.Journal of biomedical optics · 2024Article
- Beam angle optimization for proton therapy via group-sparsity based angle generation method.Medical physics · 2023Article
- Physics-/Model-Based and Data-Driven Methods for Low-Dose Computed Tomography: A survey.IEEE signal processing magazine · 2023Article
- An iterative convex relaxation method for proton LET optimization.Physics in medicine and biology · 2023Article
- Dynamic cone-beam CT reconstruction using spatial and temporal implicit neural representation learning (STINR).Physics in medicine and biology · 2023Article
- A review on Deep Learning approaches for low-dose Computed Tomography restoration.Complex & intelligent systems · 2023Article
- A selective kernel-based cycle-consistent generative adversarial network for unpaired low-dose CT denoising.Precision clinical medicine · 2022Article
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6 authors.
Funding
Abstract
Respiration-correlated CBCT, commonly called 4DCBCT, provides respiratory phase-resolved CBCT images. A typical 4DCBCT represents averaged patient images over one breathing cycle and the fourth dimension is actually breathing phase instead of time. In many clinical applications, it is desirable to obtain true 4DCBCT with the fourth dimension being time, i.e., each constituent CBCT image corresponds to an instantaneous projection. Theoretically it is impossible to reconstruct a CBCT image from a single projection. However, if all the constituent CBCT images of a 4DCBCT scan share a lot of redundant information, it might be possible to make a good reconstruction of these images by exploring their sparsity and coherence/redundancy. Though these CBCT images are not completely time resolved, they can exploit both local and global temporal coherence of the patient anatomy automatically and contain much more temporal variation information of the patient geometry than the conventional 4DCBCT. We propose in this work a computational model and algorithms for the reconstruction of this type of semi-time-resolved CBCT, called cine-CBCT, based on low rank approximation that can utilize the underlying temporal coherence both locally and globally, such as slow variation, periodicity or repetition, in those cine-CBCT images.
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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.