Microwave Imaging (MI) for breast cancer detection is a safe diagnostic method that can be used repeatedly in screening campaigns because it does not used ionizing radiations. So far it has been proven in labs and clinics with the aid of costly and bulky instrumentation tools such as a vector network analyzer. In this paper we show that it is possible to build a low-cost system using off-the-shelf components, custom-made antennas, and a Zynq programmable SoC for accelerating the image reconstruction algorithm. We prove the detection capability of our MI system with two 2D tumor phantoms with different dielectric properties. In terms of execution speed of the imaging algorithm, we obtain a speed-up of more than 30x with respect to an execution on a high-end desktop processor.
Microwave Imaging for Breast Cancer Detection: A COTS-Based Prototype / Pulimeno, Azzurra; Vacca, Marco; Casu, MARIO ROBERTO; TOBON VASQUEZ, JORGE ALBERTO; Vipiana, Francesca; JAHIER PAGLIARI, Daniele; Solimene, Raffaele; Carloni, Luca P.. - ELETTRONICO. - 409:(2017), pp. 25-34. (Intervento presentato al convegno International Conference on Applications in Electronics Pervading Industry, Environment and Society tenutosi a Roma nel 15-16 Settembre 2016) [10.1007/978-3-319-47913-2_4].
Microwave Imaging for Breast Cancer Detection: A COTS-Based Prototype
PULIMENO, AZZURRA;VACCA, MARCO;CASU, MARIO ROBERTO;TOBON VASQUEZ, JORGE ALBERTO;VIPIANA, Francesca;JAHIER PAGLIARI, DANIELE;
2017
Abstract
Microwave Imaging (MI) for breast cancer detection is a safe diagnostic method that can be used repeatedly in screening campaigns because it does not used ionizing radiations. So far it has been proven in labs and clinics with the aid of costly and bulky instrumentation tools such as a vector network analyzer. In this paper we show that it is possible to build a low-cost system using off-the-shelf components, custom-made antennas, and a Zynq programmable SoC for accelerating the image reconstruction algorithm. We prove the detection capability of our MI system with two 2D tumor phantoms with different dielectric properties. In terms of execution speed of the imaging algorithm, we obtain a speed-up of more than 30x with respect to an execution on a high-end desktop processor.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2616936