Deep learning–based 4D‐synthetic CTs from sparse‐view CBCTs for dose calculations in adaptive proton therapy
Sign Up to like & getrecommendations! Published in 2022 at "Medical Physics"
DOI: 10.1002/mp.15930
Abstract: Abstract Background Time‐resolved 4D cone beam–computed tomography (4D‐CBCT) allows a daily assessment of patient anatomy and respiratory motion. However, 4D‐CBCTs suffer from imaging artifacts that affect the CT number accuracy and prevent accurate proton dose… read more here.
Keywords: accuracy; sparse view; deep learning; dose calculations ... See more keywords
Low-Dose Sparse-View HAADF-STEM-EDX Tomography of Nanocrystals Using Unsupervised Deep Learning.
Sign Up to like & getrecommendations! Published in 2022 at "ACS nano"
DOI: 10.1021/acsnano.2c00168
Abstract: High-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) can be acquired together with energy dispersive X-ray (EDX) spectroscopy to give complementary information on the nanoparticles being imaged. Recent deep learning approaches show potential for… read more here.
Keywords: view; sparse view; deep learning; stem ... See more keywords
Superiorized algorithm for reconstruction of CT images from sparse-view and limited-angle polyenergetic data.
Sign Up to like & getrecommendations! Published in 2017 at "Physics in medicine and biology"
DOI: 10.1088/1361-6560/aa7c2d
Abstract: Recent work in CT image reconstruction has seen increasing interest in the use of total variation (TV) and related penalties to regularize problems involving reconstruction from undersampled or incomplete data. Superiorization is a recently proposed… read more here.
Keywords: reconstruction; limited angle; superiorized algorithm; sparse view ... See more keywords
Sparse-view statistical image reconstruction with improved total variation regularization for X-ray micro-CT imaging
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Instrumentation"
DOI: 10.1088/1748-0221/14/08/p08023
Abstract: Sparse-view x-ray micro computed tomography (micro-CT) reconstruction algorithms via total variation (TV) optimize the data without introducing notable noise and artifacts, resulting in significant scanning time reduction while maintaining image quality. However, due to the… read more here.
Keywords: reconstruction; image; total variation; micro ... See more keywords
PARS-NET: a novel deep learning framework using parallel residual conventional neural networks for sparse-view CT reconstruction
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Instrumentation"
DOI: 10.1088/1748-0221/17/02/p02011
Abstract: Sparse-view computed tomography (CT) is recently proposed as a promising method to speed up data acquisition and alleviate the issue of CT high dose delivery to the patients. However, traditional reconstruction algorithms are time-consuming and… read more here.
Keywords: reconstruction; neural networks; sparse view; pars net ... See more keywords
DIDR-Net: a sparse-view CT deep iterative reconstruction network with an independent detail recovery network
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Instrumentation"
DOI: 10.1088/1748-0221/18/05/p05038
Abstract: Sparse-view CT is an effective method to reduce X-ray radiation dose in clinical CT imaging. However, sparse view image reconstruction is still challenging due to highly undersampled data. To this end, we propose a new… read more here.
Keywords: network; iterative reconstruction; sparse view; reconstruction ... See more keywords
Sparse-View Cone Beam CT Reconstruction Using Data-Consistent Supervised and Adversarial Learning From Scarce Training Data
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2022.3225680
Abstract: Reconstruction of CT images from a limited set of projections through an object is important in several applications ranging from medical imaging to industrial settings. As the number of available projections decreases, traditional reconstruction techniques… read more here.
Keywords: training data; view cone; cone beam; sparse view ... See more keywords
Deep Embedding-Attention-Refinement for Sparse-View CT Reconstruction
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3221136
Abstract: Tomographic image reconstruction with deep learning is an emerging field of applied artificial intelligence. Reducing radiation dose with sparse views’ reconstruction is a significant task in cardiac imaging. Many efforts are contributing to sparse-view tomography… read more here.
Keywords: refinement; sparse view; deep embedding; reconstruction ... See more keywords
Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2018.2823768
Abstract: X-ray computed tomography (CT) using sparse projection views is a recent approach to reduce the radiation dose. However, due to the insufficient projection views, an analytic reconstruction approach using the filtered back projection (FBP) produces… read more here.
Keywords: view; deep convolutional; framing net; sparse view ... See more keywords
Enhancing sparse-view photoacoustic tomography with combined virtually parallel projecting and spatially adaptive filtering
Sign Up to like & getrecommendations! Published in 2018 at "Biomedical Optics Express"
DOI: 10.1364/boe.9.004569
Abstract: To fully realize the potential of photoacoustic tomography (PAT) in preclinical and clinical applications, rapid measurements and robust reconstructions are needed. Sparse-view measurements have been adopted effectively to accelerate the data acquisition. However, since the… read more here.
Keywords: spatially adaptive; photoacoustic tomography; view; adaptive filtering ... See more keywords
Sparse-view CBCT reconstruction via weighted Schatten p-norm minimization.
Sign Up to like & getrecommendations! Published in 2020 at "Optics express"
DOI: 10.1364/oe.404471
Abstract: A novel iterative algorithm is proposed for sparse-view cone beam computed tomography (CBCT) reconstruction based on the weighted Schatten p-norm minimization (WSNM). By using the half quadratic splitting, the sparse-view CBCT reconstruction task is decomposed… read more here.
Keywords: reconstruction; cbct reconstruction; sparse view; schatten norm ... See more keywords