PRIN 2008 - optimizAtion Methods and Software for Inverse PRoblems - PRISMA

ultima modifica 01/02/2012 10:14

Project of the Italian Ministry of University and Reasearch, grant 2008T5KA4L


In the field of data approximation, many nonlinear programming problems (NLP) represent the mathematical model of a large number of Applied Sciences problems, whose ill-posedness in the sense of Hadamard is well know in literature. Among them, the image reconstruction problems are of special interest.

The general goal of the project is to develop new models and methods for complex, large-scale imaging applications in Medicine, Astronomy and Microscopy, up to their implementation in scientific software packages.

To this end, the project coordinates and integrates the activities of five Italian research groups:

- unit of Bologna: E. Loli Piccolomini, F. Zama, G. Landi, I. Tomba;

- unit of Ferrara: V. Ruggiero, G. Zanghirati, S. Bonettini, R. Zanella, A. Giovannini;

- unit of Genova: M. Bertero, P. Boccacci;

- unit of Milano: N.A. Borghese, I. Frosio, M. Lucchese;

- unit of Modena: L. Zanni, D. Beneventano, M. Leoncini, G. Toraldo, M. Prato, A. Cornelio.

The units of Genova and Milano are working on models and techniques for medical and astronomical imaging problems since many years, while the units of Ferrara, Modena and Bologna have long term expertises on nonlinear numerical optimization and on the development of scalar and parallel algorithms for inverse problems applications.

The planned research activities include: new Bayesian models that simultaneously account for the different noise sources and their extensions to volumetric reconstructions; different approaches to the solution of denoising and deblurring problems and their comparison; the analysis and the development of new first- and  second-order optimization methods for the considered reconstruction problems and their test on real-world cases.

The  project is a continuation of the PRIN2006 project "Inverse problems in Medicine and Astronomy", where many participants to the present project were involved; the previous project has produced a meaningful number of new results, has increased the link between the research units and has defined some new open problems that surely call for a deep investigation.



The start of the project is march 2010 and its life span is two years.



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