Zobrazeno 1 - 10
of 448
pro vyhledávání: '"Herman, Gabor T"'
Purpose: A fast data-driven optimization approach, named bias-accelerated subset selection (BASS), is proposed for learning efficacious sampling patterns (SPs) with the purpose of reducing scan time in large-dimensional parallel MRI. Methods: BASS is
Externí odkaz:
http://arxiv.org/abs/2011.02322
The Fast Proximal Gradient Method (FPGM) and the Monotone FPGM (MFPGM) for minimization of nonsmooth convex functions are introduced and applied to tomographic image reconstruction. Convergence properties of the sequence of objective function values
Externí odkaz:
http://arxiv.org/abs/2008.09720
Autor:
Herman, Gabor T.
The purpose of this short paper is to identify the mathematical essence of the superiorization methodology. This methodology has been developed in recent years while attempting to solve specific application-oriented problems. Consequently, superioriz
Externí odkaz:
http://arxiv.org/abs/1909.09086
The superiorization methodology is intended to work with input data of constrained minimization problems, that is, a target function and a set of constraints. However, it is based on an antipodal way of thinking to what leads to constrained minimizat
Externí odkaz:
http://arxiv.org/abs/1908.10100
Autor:
Helou, Elias S., Zibetti, Marcelo V. W., Axel, Leon, Block, Kai Tobias, Regatte, Ravinder R., Herman, Gabor T.
Estimation of the Discrete-Time Fourier Transform (DTFT) at points of a finite domain arises in many imaging applications. A new approach to this task, the Golden Angle Linogram Fourier Domain (GALFD), is presented, together with a computationally fa
Externí odkaz:
http://arxiv.org/abs/1904.01152
Superiorization of Preconditioned Conjugate Gradient Algorithms for Tomographic Image Reconstruction
Properties of Superiorized Preconditioned Conjugate Gradient (SupPCG) algorithms in image reconstruction from projections are examined. Least squares (LS) is usually chosen for measuring data-inconsistency in these inverse problems. Preconditioned Co
Externí odkaz:
http://arxiv.org/abs/1807.10151
Algorithms for convex feasibility find or approximate a point in the intersection of given closed convex sets. Typically there are only finitely many convex sets, but the case of infinitely many convex sets also has some applications. In this context
Externí odkaz:
http://arxiv.org/abs/1807.00234