17 citations · 21 across the 5 of their papers we have counts for
6 papers
Direct Low-Dose CT Image Reconstruction on GPU using Out-Of-Core: Precision and Quality Study
M. Chillarón, G. Quintana-Ortí, V. Vidal +1
Algebraic methods applied to the reconstruction of Sparse-view Computed Tomography (CT) can provide both a high image quality and a decrease in the dose received by patients, altho…
Efficient algorithms for computing a rank-revealing UTV factorization on parallel computing architectures
N. Heavner, F. D. Igual, G. Quintana-Ortí +1
The randomized singular value decomposition (RSVD) is by now a well established technique for efficiently computing an approximate singular value decomposition of a matrix. Buildin…
Computed tomography medical image reconstruction on affordable equipment by using out-of-core techniques
Mónica Chillarón, Gregorio Quintana-Ortí, Vicente Vidal +1
As Computed Tomography (CT) scans are an essential medical test, many techniques have been proposed to reconstruct high-quality images using a smaller amount of radiation. One appr…
randUTV: A blocked randomized algorithm for computing a rank-revealing UTV factorization
Per-Gunnar Martinsson, Gregorio Quintana-Orti, Nathan Heavner
This manuscript describes the randomized algorithm randUTV for computing a so called UTV factorization efficiently. Given a matrix , the algorithm computes a factorization $A =…
Fast Algorithms for the Computation of the Minimum Distance of a Random Linear Code
Fernando Hernando, Francisco D. Igual, Gregorio Quintana-Ortí
The minimum distance of a code is an important concept in information theory. Hence, computing the minimum distance of a code with a minimum computational cost is a crucial process…
Towards an Efficient Use of the BLAS Library for Multilinear Tensor Contractions
Edoardo Di Napoli, Diego Fabregat-Traver, Gregorio Quintana-Ortì +1
Mathematical operators whose transformation rules constitute the building blocks of a multi-linear algebra are widely used in physics and engineering applications where they are ve…