R
Rosa Scapaticci
Researcher at National Research Council
Publications - 79
Citations - 1327
Rosa Scapaticci is an academic researcher from National Research Council. The author has contributed to research in topics: Microwave imaging & Imaging phantom. The author has an hindex of 16, co-authored 65 publications receiving 866 citations. Previous affiliations of Rosa Scapaticci include Mediterranea University of Reggio Calabria.
Papers
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Journal ArticleDOI
A feasibility study on microwave imaging for brain stroke monitoring
TL;DR: A simple design tool is introduced to devise guidelines to properly set the working frequency as well as to choose the optimum matching medium to facilitate the penetration of the probing wave into the head.
Journal ArticleDOI
Design and Numerical Characterization of a Low-Complexity Microwave Device for Brain Stroke Monitoring
TL;DR: The design is concerned with the determination of the optimal layout of the antennas array, namely, minimum number, positions, and polarization of the radiating elements, enabling the acquisition of an amount of data such to assure a reliable imaging.
Journal ArticleDOI
A Prototype Microwave System for 3D Brain Stroke Imaging.
Jorge A. Tobon Vasquez,Rosa Scapaticci,Giovanna Turvani,Gennaro Bellizzi,David Rodriguez-Duarte,Nadine Joachimowicz,Bernard Duchêne,Enrico Tedeschi,Mario R. Casu,Lorenzo Crocco,Francesca Vipiana +10 more
TL;DR: The open issue of monitoring patients after stroke onset is addressed here in order to provide clinicians with a tool to control the effectiveness of administered therapies during the follow-up period and a novel prototype is presented and characterized.
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Differential Microwave Imaging for Brain Stroke Followup
TL;DR: In this paper, the authors discussed 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, and showed 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.
Journal ArticleDOI
Wavelet-Based Regularization for Robust Microwave Imaging in Medical Applications
TL;DR: This paper presents a robust method for quantitative MWI in medical applications where very little, if any, a priori information on the imaging scenario is available, by employing a distorted Born iterative method and a regularization by projection technique, which reconstructs the tissue parameters using a wavelet basis expansion to represent the unknown contrast.