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Luca Zanni
University of Modena and Reggio Emilia
85Publications
17H-index
1,280Citations
Publications 87
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#1Roberto Cavicchioli (University of Modena and Reggio Emilia)H-Index: 4
#2J. Cheng Hu (University of Modena and Reggio Emilia)
Last.Luca Zanni (University of Modena and Reggio Emilia)H-Index: 17
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Digital Breast Tomosynthesis (DBT) is a modern 3D Computed Tomography X-ray technique for the early detection of breast tumors, which is receiving growing interest in the medical and scientific community. Since DBT performs incomplete sampling of data, the image reconstruction approaches based on iterative methods are preferable to the classical analytic techniques, such as the Filtered Back Projection algorithm, providing fewer artifacts. In this work, we consider a Model-Based Iterative Recons...
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#1Serena Crisci (University of Ferrara)H-Index: 2
#2Valeria Ruggiero (University of Ferrara)H-Index: 12
Last.Luca Zanni (University of Modena and Reggio Emilia)H-Index: 17
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Abstract The role of the steplength selection strategies in gradient methods has been widely investigated in the last decades. Starting from the work of Barzilai and Borwein (1988), many efficient steplength rules have been designed, that contributed to make the gradient approaches an effective tool for the large-scale optimization problems arising in important real-world applications. Most of these steplength rules have been thought in unconstrained optimization, with the aim of exploiting some...
2 CitationsSource
#1Fabio Grandi (University of Modena and Reggio Emilia)H-Index: 2
#2Luca Zanni (University of Modena and Reggio Emilia)H-Index: 17
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ABSTRACTTransdisciplinarity is characterising numerous research areas, in which natural sciences are integrated with technical and social sciences, requiring mixed methodologies for achieving full ...
1 CitationsSource
#1Silvia BonettiniH-Index: 12
#2Federica PortaH-Index: 6
Last.Luca ZanniH-Index: 17
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Minimization problems often occur in modeling phenomena dealing with real-life applications that nowadays handle large-scale data and require real-time solutions. For these reasons, among all possible iterative schemes, first-order algorithms represent a powerful tool in solving such optimization problems since they admit a relatively simple implementation and avoid onerous computations during the iterations. On the other hand, a well known drawback of these methods is a possible poor convergenc...
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#1E. Loli Piccolomini (UNIBO: University of Bologna)H-Index: 6
#2Vanna Lisa Coli (University of Modena and Reggio Emilia)H-Index: 2
Last.Luca Zanni (University of Modena and Reggio Emilia)H-Index: 17
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We propose a scaled gradient projection algorithm for the reconstruction of 3D X-ray tomographic images from limited data. The problem arises from the discretization of an ill-posed integral problem and, due to the incompleteness of the data, has infinite possible solutions. Hence, by following a regularization approach, we formulate the reconstruction problem as the nonnegatively constrained minimization of an objective function given by the sum of a fit-to-data term and a smoothed differentiab...
3 CitationsSource
#1Daniela di SerafinoH-Index: 13
#2Valeria Ruggiero (University of Ferrara)H-Index: 12
Last.Luca Zanni (University of Modena and Reggio Emilia)H-Index: 17
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Abstract The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leading to the development of effective gradient methods. Several steplength rules have been first designed for unconstrained quadratic problems and then extended to general nonlinear optimization problems. These rules share the common idea of attempting to capture, in an inexpensive way, some second-order information. However, the convergence theory of the gradient methods using the previous ...
22 CitationsSource
#1Fabio GrandiH-Index: 2
Last.Marcello PellicciariH-Index: 14
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#1Vanna Lisa ColiH-Index: 2
Last.Luca ZanniH-Index: 17
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1 CitationsSource
#1Simone RebegoldiH-Index: 3
#2Lola Bautista (CNRS: Centre national de la recherche scientifique)H-Index: 1
Last.Arturo PlataH-Index: 1
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In this paper we address the problem of estimating the phase from color images acquired with differential–interference–contrast microscopy. In particular, we consider the nonlinear and nonconvex optimization problem obtained by regularizing a least–squares–like discrepancy term with an edge–preserving functional, given by either the hypersurface potential or the total variation one. We investigate the analytical properties of the resulting objective functions, proving the existence of minimum po...
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#1Vanna Lisa ColiH-Index: 2
Last.Luca ZanniH-Index: 17
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