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

Microwave medical imaging: Potentialities and limitations of a stochastic optimization technique Author(s): Caorsi, S (Caorsi, S); Massa, A (Massa, A); Pastorino, M (Pastorino, M); Rosani, A (Rosani, A) Source: IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES Volume: 52 Issue: 8 Pages: 1909-1916 DOI: 10.1109/tmtt.2004.832016 Part: Part 2 Published: AUG 2004 Times Cited: 14 (from Web of Science) Cited References: 29 [ view related records ] Citation Map 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. Accession Number: WOS:000223051400007 Document Type: Article Language: English Author Keywords: genetic algorithms (GAs); inverse scattering; medical imaging; microwave imaging; optimization problems KeyWords Plus: BREAST-CANCER DETECTION; GENETIC ALGORITHMS; ELECTROMAGNETICS; TISSUES; MODEL Reprint Address: Rosani, A (reprint author), Univ Pavia, Dept Elect, I-27100 Pavia, Italy Addresses: 1. Univ Pavia, Dept Elect, I-27100 Pavia, Italy 2. Univ Trent, Dept Informat & Commun Technol, I-38050 Trent, Italy 3. Univ Genoa, Dept Biophys & Elect Engn, I-16145 Genoa, Italy E-mail Address: caorsi@ele.unipv.it, andrea.massa@ing.unitn.it, pastorino@dibe.unige.it Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855 USA Web of Science Category: Engineering, Electrical & Electronic Subject Category: Engineering IDS Number: 843BW ISSN: 0018-9480