Optimized first-order methods for smooth convex minimization
We introduce new optimized first-order methods for smooth unconstrained convex
minimization. Drori and Teboulle (Math Program 145 (1–2): 451–482, 2014. doi …
minimization. Drori and Teboulle (Math Program 145 (1–2): 451–482, 2014. doi …
Monotone FISTA with variable acceleration for compressed sensing magnetic resonance imaging
An improvement of the monotone fast iterative shrinkage-thresholding algorithm (MFISTA)
for faster convergence is proposed in this paper. Our motivation is to reduce the …
for faster convergence is proposed in this paper. Our motivation is to reduce the …
Generalizing the optimized gradient method for smooth convex minimization
This paper generalizes the optimized gradient method (OGM) Y. Drori and M. Teboulle,
Math. Program., 145 (2014), pp. 451--482, D. Kim and JA Fessler, Math. Program., 159 …
Math. Program., 145 (2014), pp. 451--482, D. Kim and JA Fessler, Math. Program., 159 …
Model-based reconstruction for enhanced x-ray CT of dense tri-structural isotropic particles
Tri-structural isotropic (TRISO) fuel particles are a key component of next generation nuclear
fuels. Using x-ray computed tomography (CT) to characterize TRISO particles is challenging …
fuels. Using x-ray computed tomography (CT) to characterize TRISO particles is challenging …
Model-based iterative reconstruction for neutron laminography
Neutron-based parallel-beam laminography is an important 3D characterization tool
because it can image thick specimens with unique shapes and provides a complimentary …
because it can image thick specimens with unique shapes and provides a complimentary …
Image Restoration via Group Norm-Based Structural Sparse Representation
KS Zhang, L Zhong, XY Zhang - International Journal of Pattern …, 2018 - World Scientific
Sparse representation has recently been extensively studied in the field of image
restoration. Many sparsity-based approaches enforce sparse coding on patches with certain …
restoration. Many sparsity-based approaches enforce sparse coding on patches with certain …
Fast proximal gradient methods for nonsmooth convex optimization for tomographic image reconstruction
Abstract The Fast Proximal Gradient Method (FPGM) and the Monotone FPGM (MFPGM) for
minimization of nonsmooth convex functions are introduced and applied to tomographic …
minimization of nonsmooth convex functions are introduced and applied to tomographic …
An assessment of iterative reconstruction methods for sparse ultrasound imaging
Ultrasonic image reconstruction using inverse problems has recently appeared as an
alternative to enhance ultrasound imaging over beamforming methods. This approach …
alternative to enhance ultrasound imaging over beamforming methods. This approach …
Improved acquisition and reconstruction for wavelength-resolved neutron tomography
Wavelength-resolved neutron tomography (WRNT) is an emerging technique for
characterizing samples relevant to the materials sciences in 3D. WRNT studies can be …
characterizing samples relevant to the materials sciences in 3D. WRNT studies can be …
Convolutional dictionary regularizers for tomographic inversion
There has been a growing interest in the use of data-driven regularizers to solve inverse
problems associated with computational imaging systems. The convolutional sparse …
problems associated with computational imaging systems. The convolutional sparse …