Effect Evaluation of Dexmedetomidine Intravenous Anesthesia on Postoperative Agitation in Patients with Craniocerebral Injury by Magnetic Resonance Imaging Based on Sparse Reconstruction Algorithm. [PDF]
Contrast Media Mol Imaging, 2022 Feng X, Feng X, Zhao B, Wang Y.
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Real-time dynamic vocal tract imaging using an accelerated spiral GRE sequence and low rank plus sparse reconstruction. [PDF]
Magn Reson Imaging, 2021 Feng X, Wang Z, Meyer CH.
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Sparse 3D Reconstruction via Object-Centric Ray Sampling [PDF]
We propose a novel method for 3D object reconstruction from a sparse set of views captured from a 360-degree calibrated camera rig. We represent the object surface through a hybrid model that uses both an MLP-based neural representation and a triangle ...
Favaro, Paolo, Cerkezi, Llukman
core
Split-Bregman-based sparse-view CT reconstruction [PDF]
, 2011 Total variation minimization has been extensively researched for image denoising and sparse view reconstruction. These methods show superior denoising performance for simple images with little texture, but result in texture information loss when applied ...
Goossens, Bart +6 more
core
Sparse optimization for image reconstruction in Electrical Impedance Tomography
, 2019 lectrical Impedance Tomography (EIT) can be used to obtain phase boundaries and gas holdups in multiphase flows. The main challenge in image reconstruction using EIT is the low spatial resolution.
Varanasi, Santhosh Kumar +2 more
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Sparse-View CT Reconstruction Based on Improved Re-Sidual Network
, 2019 With the development of CT imaging, people have higher requirements for the quality of CT image reconstruction. It is desirable to use as low as reasonably achievable X-ray dose while meeting the quality of imaging requirements.
Shipeng Xie +7 more
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A heuristic for sparse signal reconstruction.
, 2012 Compressive Sampling (CS) is a new method of signal acquisition and reconstruction from frequency data which do not follow the basic principle of the Nyquist-Shannon sampling theory. This new method allows reconstruction of the signal from substantially fewer measurements than those required by conventional sampling methods.
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Reconstruction of Sparse Sampled Images with Deep Learning
, 2021 The main goal of this thesis was to increase reconstruction quality of sparse sampled microscopic images by using neural networks. The thesis will cover various approaches for image reconstruction and will also include descriptions of implementations ...
Le, Hoang Anh
core
Sparse reconstruction of log-conductivity in current density impedance tomography. [PDF]
J Math Imaging Vis, 2020 Gupta M, Mishra RK, Roy S.
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Accelerated Stimulated Raman Projection Tomography by Sparse Reconstruction From Sparse-View Data. [PDF]
IEEE Trans Biomed Eng, 2020 Chen X +10 more
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