E
Elias S. Helou
Researcher at University of São Paulo
Publications - 41
Citations - 403
Elias S. Helou is an academic researcher from University of São Paulo. The author has contributed to research in topics: Iterative reconstruction & Convex optimization. The author has an hindex of 11, co-authored 40 publications receiving 321 citations. Previous affiliations of Elias S. Helou include Spanish National Research Council.
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Similarity Preserving Snippet-Based Visualization of Web Search Results
Erick Gomez-Nieto,Frizzi San Roman,Paulo Pagliosa,Wallace Casaca,Elias S. Helou,Maria Cristina Ferreira de Oliveira,Luis Gustavo Nonato +6 more
TL;DR: A visualization technique to display the results of web queries aimed at overcoming limitations in particular situations by employing a multidimensional projection to derive two-dimensional layouts of the query search results that preserve text similarity relations, or neighborhoods.
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A Backprojection Slice Theorem for Tomographic Reconstruction
TL;DR: A new fast backprojection operator is proposed for the processing of tomographic data, providing a low-cost algorithm for this task and is compared against other fast transposition techniques, using real and simulated large data sets.
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Accelerating Overrelaxed and Monotone Fast Iterative Shrinkage-Thresholding Algorithms With Line Search for Sparse Reconstructions
TL;DR: The use of fast line search is extended to the monotone fast iterative shrinkage-threshold algorithm (MFISTA) and some of its variants and shows through numerical results that line search improves their performance for tomographic high-resolution image reconstruction.
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Monotone FISTA With Variable Acceleration for Compressed Sensing Magnetic Resonance Imaging
TL;DR: An improvement of the monotone fast iterative shrinkage-thresholding algorithm (MFISTA) for faster convergence is proposed in this paper to reduce the reconstruction time of compressed sensing problems in magnetic resonance imaging.
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Mesh-Free Discrete Laplace-Beltrami Operator
TL;DR: This work proposes a new discretization method for the Laplace–Beltrami operator defined on point‐based surfaces that uses the eigenstructure of the discrete operator for filtering and shape segmentation and results in numerically stable discrete operators.