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   Articles with "sparse view" as a keyword



Deep learning–based 4D‐synthetic CTs from sparse‐view CBCTs for dose calculations in adaptive proton therapy

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recommendations! 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.

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recommendations! 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.

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recommendations! 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

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recommendations! 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

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recommendations! 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

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recommendations! 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 image reconstruction with total-variation minimization applied to sparsely sampled projection data from SiPM-based photon-counting CT

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recommendations! Published in 2024 at "Journal of Instrumentation"

DOI: 10.1088/1748-0221/19/02/c02010

Abstract: We constructed a sparse-view computed tomography (CT) system that combines a compressed sensing (CS)-based image-reconstruction algorithm and SiPM-based photon-counting (PC) CT. CS-based image-reconstruction algorithms have been extensively studied for X-ray CT image reconstruction using fewer… read more here.

Keywords: projection data; based image; image; sparse view ... See more keywords

A Dual-Domain Diffusion Model for Sparse-View CT Reconstruction

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recommendations! Published in 2024 at "IEEE Signal Processing Letters"

DOI: 10.1109/lsp.2024.3392690

Abstract: To reduce the radiation dose, sparse-view computed tomography (CT) reconstruction has been proposed, aiming to recover high-quality CT images from sparsely sampled sinogram. To eliminate the artifacts present in sparse-view CT images, a new dual-domain… read more here.

Keywords: view; dual domain; domain diffusion; sparse view ... See more keywords

Sparse-View Cone Beam CT Reconstruction Using Data-Consistent Supervised and Adversarial Learning From Scarce Training Data

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recommendations! 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
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Deep Embedding-Attention-Refinement for Sparse-View CT Reconstruction

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recommendations! 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

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recommendations! 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