Abstract:Purpose:
In microwave breast cancer detection, it is often beneficial to arrange sensors in close proximity to the breast. The resultant coupling generally changes the antenna response. As an a priori characterization of the radio frequency system becomes difficult, this can lead to severe degradation of the detection efficacy. The purpose of this paper is to demonstrate the advantages of adopting an interferometric multiple signal classification (I‐MUSIC) approach due to its limited dependence from a priori i… Show more
“…I-MUSIC has been numerically and experimentally assessed in [26] using a Vector Network Analyzer (VNA) for probing a breast phantom and collecting the corresponding scattered field. Also, a PC has been used for processing the acquired data.…”
Section: Background and Related Workmentioning
confidence: 99%
“…• We show that I-MUSIC can run on an embedded platform, enhanced with an FPGA, more than 20x faster than on a server-grade CPU. All the reported results have been obtained using an existing MI algorithm, I-MUSIC, whose detection effectiveness has been proven already [25] [26]. This is the paper organization.…”
Microwave imaging is an emerging breast cancer diagnostic technique, which aims at complementing already established methods like mammography, magnetic resonance imaging, and ultrasound. It offers two striking advantages: no-risk for the patient and potential low-cost for national health systems. So far, however, the prototypes developed for validation in labs and clinics used costly lab instruments such as a vector network analyzer (VNA). Moreover, the CPU time required by complex image reconstruction algorithms may not be compatible with the duration of a medical examination. In this paper, both these issues are tackled. Indeed, we present a prototype system based on low-cost and off-the-shelf microwave components, custom-made antennas, and a small form-factor processing system with an embedded field-programmable gate array for accelerating the execution of the imaging algorithm. We show that our low-cost system can compete with an expensive VNA in terms of accuracy, and it is more than 20x faster than a high-performance server at image reconstruction.
“…I-MUSIC has been numerically and experimentally assessed in [26] using a Vector Network Analyzer (VNA) for probing a breast phantom and collecting the corresponding scattered field. Also, a PC has been used for processing the acquired data.…”
Section: Background and Related Workmentioning
confidence: 99%
“…• We show that I-MUSIC can run on an embedded platform, enhanced with an FPGA, more than 20x faster than on a server-grade CPU. All the reported results have been obtained using an existing MI algorithm, I-MUSIC, whose detection effectiveness has been proven already [25] [26]. This is the paper organization.…”
Microwave imaging is an emerging breast cancer diagnostic technique, which aims at complementing already established methods like mammography, magnetic resonance imaging, and ultrasound. It offers two striking advantages: no-risk for the patient and potential low-cost for national health systems. So far, however, the prototypes developed for validation in labs and clinics used costly lab instruments such as a vector network analyzer (VNA). Moreover, the CPU time required by complex image reconstruction algorithms may not be compatible with the duration of a medical examination. In this paper, both these issues are tackled. Indeed, we present a prototype system based on low-cost and off-the-shelf microwave components, custom-made antennas, and a small form-factor processing system with an embedded field-programmable gate array for accelerating the execution of the imaging algorithm. We show that our low-cost system can compete with an expensive VNA in terms of accuracy, and it is more than 20x faster than a high-performance server at image reconstruction.
“…15 Images formed using monostatic datasets usually exhibit a higher focal quality, whereas multistatic approaches yield datasets with greater sensitivity and specificity. Currently, the majority of BMR image reconstruction is performed using time-domain processing methods, which perform an approximation of the phase behavior of the signal along the scan trajectory 19 that may generate images with artifacts 15,16 due to phase aberrations. 19 During the last five years, the use of MUSIC reconstruction algorithms has also been proposed for BMR image reconstruction.…”
Section: Introductionmentioning
confidence: 99%
“…Currently, the majority of BMR image reconstruction is performed using time-domain processing methods, which perform an approximation of the phase behavior of the signal along the scan trajectory 19 that may generate images with artifacts 15,16 due to phase aberrations. 19 During the last five years, the use of MUSIC reconstruction algorithms has also been proposed for BMR image reconstruction. 20,21 These techniques exhibit excellent noise reduction, and their feasibility has been assessed in experimental datasets.…”
The images generated by the proposed method show that multistatic holography is capable of forming spatially accurate images in real-time with signal to clutter levels and contrast values higher than other published monostatic and multistatic cylindrical radar reconstruction approaches. In comparison to the monostatic holographic approach, the images generated by the proposed multistatic approach had SCR values that were at least 50% higher. The multistatic images had CCR and TFRR values at least 200% greater than those formed using a monostatic approach.
“…This application is of high relevance in diagnostic operations not only to assess the structural stability of concrete structures [1,2] but also to inspect them after disaster events (e.g., earthquakes) [3]. Another very important field of application concerns early breast cancer detection where the tumour actually can be considered to be a small scatterer [4].…”
Many inverse scattering problems concern the detection and localisation of point-like scatterers which are sparsely enclosed within a prescribed investigation domain. Therefore, it looks like a good option to tackle the problem by applying reconstruction methods that are properly tailored for such a type of scatterers or that naturally enforce sparsity in the reconstructions. Accordingly, in this paper we compare the time reversal-MUSIC and the compressed sensing. The study develops through numerical examples and focuses on the role of noise in data and mutual coupling between the scatterers.
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