Results 11 to 20 of about 68,766 (311)
Multi-Scale Learned Iterative Reconstruction [PDF]
IEEE Transactions on Computational Imaging, 2020 Model-based learned iterative reconstruction methods have recently been shown to outperform classical reconstruction algorithms. Applicability of these methods to large scale inverse problems is however limited by the available memory for training and extensive training times, the latter due to computationally expensive forward models.
Andreas Hauptmann +3 more
core +8 more sources
Data in Brief, 2017 This article describes a quantitative evaluation of visualizing small vessels using several image reconstruction methods in computed tomography. Simulated vessels with diameters of 1–6 mm made by 3D printer was scanned using 320-row detector computed ...
Toru Higaki +7 more
doaj +2 more sources
Iterative Reconstruction of Signals on Graph [PDF]
IEEE Signal Processing Letters, 2020 We propose an iterative algorithm to interpolate graph signals from only a partial set of samples. Our method is derived from the well known Papoulis-Gerchberg algorithm by considering the optimal value of a constant involved in the iteration step. Compared with existing graph signal reconstruction algorithms, the proposed method achieves similar or ...
Emanuele Brugnoli +2 more
openaire +5 more sources
Optimizing computed tomography image reconstruction for focal hepatic lesions: Deep learning image reconstruction vs iterative reconstruction [PDF]
HeliyonBackground: Deep learning image reconstruction (DLIR) is a novel computed tomography (CT) reconstruction technique that minimizes image noise, enhances image quality, and enables radiation dose reduction.
Varin Jaruvongvanich +10 more
doaj +2 more sources
Photoacoustics, 2023 Iterative reconstruction has demonstrated superior performance in medical imaging under compressed, sparse, and limited-view sensing scenarios. However, iterative reconstruction algorithms are slow to converge and rely heavily on hand-crafted parameters ...
Ko-Tsung Hsu +2 more
doaj +1 more source
Journal of Integrative Neuroscience, 2021 To evaluate the ability of a commercialized deep learning reconstruction technique to depict intracranial vessels on the brain computed tomography angiography and compare the image quality with filtered-back-projection and hybrid iterative ...
Chuluunbaatar Otgonbaatar +5 more
doaj +1 more source
GNSS troposphere tomography based on two-step reconstructions using GPS observations and COSMIC profiles [PDF]
Annales Geophysicae, 2013 Traditionally, balloon-based radiosonde soundings are used to study the spatial distribution of atmospheric water vapour. However, this approach cannot be frequently employed due to its high cost. In contrast, GPS tomography technique can obtain water
P. Xia, P. Xia, C. Cai, Z. Liu
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Phase Reconstruction with Iterated Hilbert Transforms [PDF]
, 2021 We present a study dealing with a novel phase reconstruction method based on iterated Hilbert transform embeddings. We show results for the Stuart-Landau oscillator observed by generic observables. The benefits for reconstruction of the phase response curve a presented and the method is applied in a setting where the observed system is pertubred by ...
Erik Gengel, Arkady Pikovsky
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SoftwareX, 2022 The challenge of processing big data effectively and efficiently is crucial for many synchrotron facilities which can collect up to several petabytes of data annually.
Daniil Kazantsev +2 more
doaj +1 more source
Iterative Reconstruction of Memory Kernels [PDF]
Journal of Chemical Theory and Computation, 2017 In recent years, it has become increasingly popular to construct coarse-grained models with non-Markovian dynamics to account for an incomplete separation of time scales. One challenge of a systematic coarse-graining procedure is the extraction of the dynamical properties, namely, the memory kernel, from equilibrium all-atom simulations.
Gerhard Jung +2 more
openaire +3 more sources