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 constructed 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 an "object" modeling a tumor.

Microwave medical imaging: Potentialities and limitations of a stochastic optimization technique

CAORSI, SALVATORE;MASSA, ANDREA;PASTORINO, MATTEO;
2004-01-01

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 constructed 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 an "object" modeling a tumor.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/209243
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