eprintid: 566 rev_number: 6 eprint_status: archive userid: 5 dir: disk0/00/00/05/66 datestamp: 2004-09-01 lastmod: 2013-07-04 13:23:33 status_changed: 2013-07-04 13:23:33 type: techreport metadata_visibility: show item_issues_count: 0 creators_name: Caorsi, Salvatore creators_name: Massa, Andrea creators_name: Pastorino, Matteo creators_name: Rosani, Andrea title: Microwave Medical Imaging: Potentialities and Limitations of a Stochastic Optimization Technique ispublished: submitted subjects: TU full_text_status: public abstract: An approach based on a stochastic optimization technique is proposed for medical microwave imaging. The approach is based on the integral equations of the electromagnetic inverse scattering. After discretization of the continuous model, the problem solution is recast as a global optimization problem. A functional is costructed on the basis of a Markov random field model and minimized by a genetic algorithm. In order to reduce the computational load, a model of the cross section of the biological body is considered. In this way, the investigation area is limited by separating the scattering contribution of a fixed region under test from those of other parts of the model. Some preliminary results concerning a two-dimensional model of a human thorax are reported. Such a biological structure is inspected by the proposed tomographic approach in order to detect and localize the presence of and "object" modeling a tumor. date: 2004-08 date_type: published institution: University of Trento department: informaticat refereed: FALSE referencetext: 1. L. E. Larsen and J. H. Jacobi, Medical Applications of Microwave Imaging, 1986 :IEEE Press 2. G. N. Hounsfield, "Computerized transverse axial scanning (tomography). I. Description of system", Br. J. Radiol., vol. 46, pp.1016 -1024 1973 3. J. F. Greenleaf, et al., P. S. 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Microwave Power, vol. 16, pp.107 -119 1981 citation: Caorsi, Salvatore and Massa, Andrea and Pastorino, Matteo and Rosani, Andrea (2004) Microwave Medical Imaging: Potentialities and Limitations of a Stochastic Optimization Technique. [Technical Report] (Submitted) document_url: http://www.eledia.org/students-reports/566/1/DIT-04-079.pdf