Detecting Point-Like Sources of Unknown Frequency Spectra

Solimene, Raffaele; Ruvio, Giuseppe; Dell’Aversano, Angela; Cuccaro, Antonio; Ammann, Max J.; Pierri, Rocco

doi:10.2528/pierb13030414

Cited by 17 publications

(19 citation statements)

References 18 publications

(23 reference statements)

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“…This is mainly due to the mismatch between the adopted equivalent breast permittivity in the reference Green's function and the actual unknown permittivity mapping of the detection scene. The dependence of this delocalization effect from such mismatch was analyzed by Solimene et al 24 in controlled canonical scenarios and it draws the attention toward further developments of the I-MUSIC approach.…”

Section: Discussionmentioning

confidence: 99%

“…To this end, the I-MUSIC is proposed. 24 First, for each adopted frequency, the correlation matrix is obtained as…”

Section: The Imaging Proceduresmentioning

confidence: 99%

“…Rank deficiency of R( f n f ) entails some limitations on the achievable performance and uniqueness problems, especially with a low number of scanning positions. 24 In order to overcome these limitations, pseudospectra obtained at different frequencies can be incoherently combined as suggested by Yavuz and Teixeira 34 By doing so, the so-called wideband MUSIC is obtained…”

Section: The Imaging Proceduresmentioning

confidence: 99%

“…More specifically, images obtained at different frequencies are multiplicatively mixed with each other. Theoretical details and performance assessment were addressed by Solimene et al 24 Preliminary numerical results on a breast scenario were reported by Ruvio et al 25 In this study, a 2D numerical mostly fatty breast model was derived from a MRI scan according to the Wisconsin's repository. 26 It is shown that the method succeeds in detecting a low-contrast tumor when the antenna response is completely neglected in the imaging procedure.…”

Section: Introductionmentioning

confidence: 98%

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Breast cancer detection using interferometric MUSIC: Experimental and numerical assessment

Ruvio¹,

Solimene

Cuccaro

et al. 2014

Medical Physics

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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 information on the antenna. The performance of I‐MUSIC detection was measured in terms of signal‐to‐clutter ratio (SCR), signal‐to‐mean ratio (SMR), and spatial displacement (SD) and compared to other common linear noncoherent imaging methods, such as migration and the standard wideband MUSIC (WB‐MUSIC) which also works when the antenna is not accounted for. Methods: The data were acquired by scanning a synthetic oil‐in‐gelatin phantom that mimics the dielectric properties of breast tissues across the spectrum 1–3 GHz using a proprietary breast microwave multi‐monostatic radar system. The phantom is a multilayer structure that includes skin, adipose, fibroconnective, fibroglandular, and tumor tissue with an adipose component accounting for 60% of the whole structure. The detected tumor has a diameter of 5 mm and is inserted inside a fibroglandular region with a permittivity contrast εr‐tumor/εr‐fibroglandular < 1.5 over the operating band. Three datasets were recorded corresponding to three antennas with different coupling mechanisms. This was done to assess the independence of the I‐MUSIC method from antenna characterizations. The datasets were processed by using I‐MUSIC, noncoherent migration, and wideband MUSIC under equivalent conditions (i.e., operative bandwidth, frequency samples, and scanning positions). SCR, SMR, and SD figures were measured from all reconstructed images. In order to benchmark experimental results, numerical simulations of equivalent scenarios were carried out by using CST Microwave Studio. The three numerical datasets were then processed following the same procedure that was designed for the experimental case. Results: Detection results are presented for both experimental and numerical phantoms, and higher performance of the I‐MUSIC method in comparison with the WB‐MUSIC and noncoherent migration is achieved. This finding is confirmed for the three different antennas in this study. Although a delocalization effect occurs, experimental datasets show that the signal‐to‐clutter ratio and the signal‐to‐mean performance with the I‐MUSIC are at least 5 and 2.3 times better than the other methods, respectively. The numerical datasets calculated on an equivalent phantom for cross‐testing confirm the improved performance of the I‐MUSIC in terms of SCR and SMR. In numerical simulations, the delocalization effect is dramatically reduced up to an SD value of 1.61 achieved with the I‐MUSIC in combination with the antipodal Vivaldi antenna. This shows that mechanical uncertainties are the main re...

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Section: Discussionmentioning

confidence: 99%

“…To this end, the I-MUSIC is proposed. 24 First, for each adopted frequency, the correlation matrix is obtained as…”

Section: The Imaging Proceduresmentioning

confidence: 99%

Section: The Imaging Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

See 2 more Smart Citations

Breast cancer detection using interferometric MUSIC: Experimental and numerical assessment

Ruvio¹,

Solimene

Cuccaro

et al. 2014

Medical Physics

Self Cite

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“…Until now, this fact has been examined through the results of numerical simulations. In recent work [19], an analysis of MUSIC for detecting point-like scatterers has been considered but a suitable mathematical theory about the structure of MUSIC-type imaging functional for detecting cracks must be established to diagnose such phenomenon.…”

Section: Introductionmentioning

confidence: 99%

Appearance of inaccurate results in the MUSIC algorithm with inappropriate wavenumber

Park

2017

Journal of Inverse and Ill-Posed Problems

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Abstract. MUltiple SIgnal Classification (MUSIC) is a well-known non-iterative location detection algorithm for small, perfectly conducting cracks in inverse scattering problems. However, when the applied wavenumbers are unknown, inaccurate locations of targets are extracted by MUSIC with inappropriate wavenumbers, a fact that has been confirmed by numerical simulations. To date, the reason behind this phenomenon has not been theoretically investigated. Motivated by this fact, we identify the structure of MUSIC-type imaging functionals with inappropriate wavenumbers by establishing a relationship with Bessel functions of order zero of the first kind. This result explains the reasons for inaccurate results. Various results of numerical simulations with noisy data support the identified structure of MUSIC.

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MUSIC-type imaging of perfectly conducting cracks in limited-view inverse scattering problems

Joh

Kwon

Park

2014

Applied Mathematics and Computation

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Detecting Point-Like Sources of Unknown Frequency Spectra

Cited by 17 publications

References 18 publications

Breast cancer detection using interferometric MUSIC: Experimental and numerical assessment

Breast cancer detection using interferometric MUSIC: Experimental and numerical assessment

Appearance of inaccurate results in the MUSIC algorithm with inappropriate wavenumber

MUSIC-type imaging of perfectly conducting cracks in limited-view inverse scattering problems

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