The ELEDIA Research Center is pleased to announce that a new paper has been published in the Electronics – Special Issue on ‘New Trends and Future Challenges in Computational Microwave Imaging’:
M. Salucci, A. Polo, and J. Vrba, “Multi-step learning-by-examples strategy for real-time brain stroke microwave scattering data inversion,” Electronics – Special Issue on ‘New Trends and Future Challenges in Computational Microwave Imaging’, vol. 10, no. 1, pp. 1-17, January 2021 (DOI: 10.3390/electronics10010095).
Abstract:
This work deals with the computationally-efficient inversion of microwave scattering data for brain stroke detection and monitoring. The proposed multi-step approach is based on the Learning-by-Examples (LBE) paradigm and naturally matches the stages and time constraints of an effective clinical diagnosis. Stroke detection, identification, and localization are solved with real-time performance through support vector machines (SVMs) operating both in binary/multi-class classification and in regression modalities. Experimental results dealing with the inversion of laboratory-controlled data are shown to verify the effectiveness of the proposed multi-step LBE methodology and prove its suitability as a viable alternative/support to standard medical diagnostic methods.
The paper can be downloaded at the following link https://doi.org/10.1109/LAWP.2020.3010410
Contact us at contact@eledia.org for the pre-print version of the manuscript.
