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Convex optimization algorithms in medical image reconstruction—in the age of AI
The past decade has seen the rapid growth of model based image reconstruction (MBIR)
algorithms, which are often applications or adaptations of convex optimization algorithms …
algorithms, which are often applications or adaptations of convex optimization algorithms …
Limited-Angle CT Reconstruction via the Minimization
In this paper, we consider minimizing the L_1/L_2 term on the gradient for a limited-angle
scanning problem in computed tomography (CT) reconstruction. We design a specific …
scanning problem in computed tomography (CT) reconstruction. We design a specific …
L 1−2 minimization for exact and stable seismic attenuation compensation
Frequency-dependent amplitude absorption and phase velocity dispersion are typically
linked by the causality-imposed Kramers–Kronig relations, which inevitably degrade the …
linked by the causality-imposed Kramers–Kronig relations, which inevitably degrade the …
A new relaxed CQ algorithm for solving split feasibility problems in Hilbert spaces and its applications.
A Gibali, DT Mai - Journal of Industrial & Management …, 2019 - search.ebscohost.com
Inspired by the works of López et al.[21] and the recent paper of Dang et al.[15], we devise a
new inertial relaxation of the CQ algorithm for solving Split Feasibility Problems (SFP) in real …
new inertial relaxation of the CQ algorithm for solving Split Feasibility Problems (SFP) in real …
Multi-channel nuclear norm minus Frobenius norm minimization for color image denoising
Color image denoising is frequently encountered in various image processing and computer
vision tasks. One traditional strategy is to convert the RGB image to a less correlated color …
vision tasks. One traditional strategy is to convert the RGB image to a less correlated color …
Sparse signal recovery with minimization of 1-norm minus 2-norm
The key aim of compressed sensing is to stably recover a K-sparse signals x from a linear
model y= Ax+ v, where v is a noise vector. Minimization of∥ x∥ 1-∥ x∥ 2 is a recently …
model y= Ax+ v, where v is a noise vector. Minimization of∥ x∥ 1-∥ x∥ 2 is a recently …
Total variation--based phase retrieval for Poisson noise removal
Phase retrieval plays an important role in vast industrial and scientific applications. We
consider a noisy phase retrieval problem in which the magnitudes of the Fourier transform …
consider a noisy phase retrieval problem in which the magnitudes of the Fourier transform …
Blind ptychographic phase retrieval via convergent alternating direction method of multipliers
Ptychography has risen as a reference X-ray imaging technique: it achieves resolutions of
one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or …
one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or …
The proximal operator of the piece-wise exponential function
This letter characterizes the proximal operator of the piece-wise exponential function with a
given shape parameter, which is a popular non-convex surrogate of the-norm in support …
given shape parameter, which is a popular non-convex surrogate of the-norm in support …
Quaternion nuclear norm minus frobenius norm minimization for color image reconstruction
Color image restoration methods typically represent images as vectors in Euclidean space
or combinations of three monochrome channels. However, they often overlook the …
or combinations of three monochrome channels. However, they often overlook the …