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International Journal of Antennas and Propagation
Volume 2014 (2014), Article ID 312528, 11 pages
Research Article

Differential Microwave Imaging for Brain Stroke Followup

1IREA, National Research Council of Italy, Via Diocleziano 328, 80124 Napoli, Italy
2DIIES, University Mediterranea of Reggio Calabria, Via Graziella, Loc. Feo di Vito, 89124 Reggio Calabria, Italy
3DIETI, Federico II University of Naples, Via Claudio 21, 80125 Napoli, Italy

Received 2 July 2013; Revised 15 November 2013; Accepted 27 November 2013; Published 2 January 2014

Academic Editor: Andrea Borsic

Copyright © 2014 R. Scapaticci et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper deals with the possibility of adopting microwave imaging to continuously monitor a patient after the onset of a brain stroke, with the aim to follow the evolution of the disease, promptly counteract its uncontrolled growth, and possibly support decisions in the clinical treatment. In such a framework, the assessed techniques for brain stroke diagnosis are indeed not suitable to pursue this goal. Conversely, microwave imaging can provide a diagnostic tool able to follow up the disease’s evolution, while relying on a relatively low cost and portable apparatus. The proposed imaging procedure is based on a differential approach which requires the processing of scattered field data measured at different time instants. By means of a numerical analysis dealing with synthetic data generated for realistic anthropomorphic phantoms, we address some crucial issues for the method’s effectiveness. In particular, we discuss the role of patient-specific information and the effect of inaccuracies in the measurement procedure, such as an incorrect positioning of the probes between two different examinations. The observed results show that the proposed technique is indeed feasible, even when a simple, nonspecific model of the head is exploited and is robust against the above mentioned inaccuracies.