Microwave Technology for Brain Imaging and Monitoring: Physical Foundations, Potential and Limitations

Scapaticci, Rosa; Bjelogrlic, Mina; Vasquez, J. A. Tobon; Vipiana, F.; Mattes, Michael; Crocco, Lorenzo

doi:10.1007/978-3-319-75007-1_2

Cited by 26 publications

(19 citation statements)

References 24 publications

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“…However, these TMMs are hard to reconfigure to account for changes associated with the shape of the anatomical lesion compared to liquid-based TMMs [13]. There has been a limited development on bone mimicking phantoms with only simplified homogeneous structures reported for head models [13], [21]. However, to the best of authors' knowledge, no study has ever reported TMMs for cortical and trabecular bones separately for the application of bone imaging.…”

mentioning

confidence: 99%

Anthropomorphic Calcaneus Phantom for Microwave Bone Imaging Applications

Amin

Shahzad

Kelly

et al. 2021

IEEE J. Electromagn. RF Microw. Med. Biol.

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Tissue-Mimicking Mixtures and Anthropomorphic Calcaneus Phantom for Bone Imaging Applications Take-Home Messages• This work presents tissue-mimicking mixtures to mimic the dielectric properties of skin, muscle, cortical bone, and trabecular bone. • Anatomically realistic phantoms must be considered as preclinical testing of the microwave imaging system.• The tissue-mimicking mixtures and the 3D-printed structures presented in this work can be used as a valuable test platform for a microwave imaging system for bone health monitoring. • The recipe of tissue-mimicking mixtures for cortical bone and trabecular bone is presented separately.• This study has proposed separate tissue-mimicking mixtures for cortical bone and trabecular bone.

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mentioning

confidence: 99%

Anthropomorphic Calcaneus Phantom for Microwave Bone Imaging Applications

Amin

Shahzad

Kelly

et al. 2021

IEEE J. Electromagn. RF Microw. Med. Biol.

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“…The choice of the working frequency range and the dielectric characteristics of the coupling medium are strictly related to the final use of the realized microwave imaging system, i.e., brain stroke monitoring. According to previous theoretical studies [20,21], the transmission coefficient through a layered medium representing the different tissues of the brain exhibits a "forbidden" band between around 1.5 GHz and 2.5 GHz. The frequency behavior of the transmission coefficient depends slightly on the dielectric characteristics of the International Journal of Antennas and Propagation coupling medium; in particular, the starting frequency of the forbidden band is a bit higher if its relative permittivity is around 20 or lower.…”

Section: Frequency Range and Couplingmentioning

confidence: 87%

Design and Experimental Assessment of a 2D Microwave Imaging System for Brain Stroke Monitoring

Vasquez

Scapaticci

Turvani

et al. 2019

International Journal of Antennas and Propagation

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The aim of this paper is to present and experimentally verify the first prototype of a microwave imaging system specifically designed and realized for the continuous monitoring of patients affected by brain stroke, immediately after its onset and diagnosis. The device is a 2D version of the 3D system, currently under construction, and consists of an array of 12 printed monopole antennas connected to a two-port vector network analyzer through a switching matrix so that each antenna can act as a transmitter or receiver, thereby allowing the acquisition of the entire multistatic multiview scattering matrix required for the imaging. The system has been experimentally tested on 2D phantoms with electric properties mimicking the brain. The presence and the evolution of the stroke have been reproduced by filling a proper cavity in the phantom with a liquid having the electric properties of blood. A differential approach has been adopted by acquiring the scattering matrix before and after the filling of the blood cavity. The so achieved differential dataset has been processed by means of a linear imaging algorithm in order to reconstruct the stroke location and dimension. Moreover, the effect of pre- and postprocessing operations on the measured data is investigated. A good agreement has been obtained between the reconstructions and the actual scenario. As a final remark, it is worth noting that the entire data acquisition and processing are sufficiently fast to allow a real-time monitoring.

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“…The unknown dielectric properties are estimated by using a parametric model of complex permittivity over the desired frequency band. To this end, this study implemented the DBIM approximation method, which linearizes the EM scattering wave equation by replacing the total field with a known incident field [21]. The incident field is estimated at each iteration of the DBIM algorithm in the presence of known background.…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…The EM inverse scattering problem is inherently ill-posed and non-linear [1]. The regularization and linearization techniques are applied to deal with non-linearity and ill-posedness of the EM inverse scattering problem [19,21]. To this end, various non-linear iterative techniques have been proposed in the literature, such as the forward-backward time-stepping method [22], Gauss-Newton optimization approach [12,23], and microwave tomography using the dielectric Debye model [24].…”

Section: Introductionmentioning

confidence: 99%

Microwave Bone Imaging: A Preliminary Investigation on Numerical Bone Phantoms for Bone Health Monitoring

Amin

Shahzad

O’Halloran

et al. 2020

Sensors

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Microwave tomography (MWT) can be used as an alternative modality for monitoring human bone health. Studies have found a significant dielectric contrast between healthy and diseased human trabecular bones. A set of diverse bone phantoms were developed based on single-pole Debye parameters of osteoporotic and osteoarthritis human trabecular bones. The bone phantoms were designed as a two-layered circular structure, where the outer layer mimics the dielectric properties of the cortical bone and the inner layer mimics the dielectric properties of the trabecular bone. The electromagnetic (EM) inverse scattering problem was solved using a distorted Born iterative method (DBIM). A compressed sensing-based linear inversion approach referred to as iterative method with adaptive thresholding for compressed sensing (IMATCS) has been employed for solving the underdetermined set of linear equations at each DBIM iteration. To overcome the challenges posed by the ill-posedness of the EM inverse scattering problem, the L2-based regularization approach was adopted in the amalgamation of the IMATCS approach. The simulation results showed that osteoporotic and osteoarthritis bones can be differentiated based on the reconstructed dielectric properties even for low values of the signal-to-noise ratio. These results show that the adopted approach can be used to monitor bone health based on the reconstructed dielectric properties.

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Microwave Technology for Brain Imaging and Monitoring: Physical Foundations, Potential and Limitations

Cited by 26 publications

References 24 publications

Anthropomorphic Calcaneus Phantom for Microwave Bone Imaging Applications

Anthropomorphic Calcaneus Phantom for Microwave Bone Imaging Applications

Design and Experimental Assessment of a 2D Microwave Imaging System for Brain Stroke Monitoring

Microwave Bone Imaging: A Preliminary Investigation on Numerical Bone Phantoms for Bone Health Monitoring

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