A Rapid Medical Microwave Tomography Based on Partial Differential Equations

Afsari, Arman; Abbosh, Amin; Rahmat‐Samii, Y.

doi:10.1109/tap.2018.2855642

Cited by 24 publications

(8 citation statements)

References 20 publications

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“…In 3D modeling, significant approximations are usually implemented within the integral equations to reduce the computational burden associated with the Green's function. To avoid the undesirable effects produced by these approximations, Ansari et al introduced a partial differential equation framework to implement faster reconstructions that is crucial in emergency scenarios like stroke detection [99].…”

Section: Regularization and Optimization Schemesmentioning

confidence: 99%

An Overview of Microwave Imaging for Breast Tumor Detection

Benny¹,

Anjit²,

Mythili³

2020

PIER B

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Microwave imaging (MWI) is a non-ionizing, non-invasive and an upcoming affordable medical imaging modality. Over the last few decades, MWI has invited active research towards biomedical imaging, with special focus on breast tumor detection. After long years of intense research and clinical trials, a breast tumour monitoring unit based on MWI is finally entering clinical imaging scenarios. In this manuscript, the vast literature in MWI to date has been consolidated, and an indetail study of the state-of-the-art for breast tumor detection has been presented. The hurdles faced during clinical trials are discussed, and their possible solutions and future directions for a fast transition into clinical imaging have been presented. It is hoped that this paper can serve as a guide for MWI researchers and practitioners, especially those new to the field to comprehend the potential of MWI as a viable imaging tool for breast imaging.

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Section: Regularization and Optimization Schemesmentioning

confidence: 99%

An Overview of Microwave Imaging for Breast Tumor Detection

Benny¹,

Anjit²,

Mythili³

2020

PIER B

View full text Add to dashboard Cite

show abstract

“…As far as stroke imaging is concerned, several systems have been proposed, which are at different stages of development [5][6][7][8]. In particular, the BRIM G2 developed at EMTensor [5] for brain stroke tomography and the device developed at the University of Queensland, devoted to intracranial hemorrhage imaging [6,9,10], have been both tested on phantoms as well as on some volunteers with encouraging results.…”

Section: Introductionmentioning

confidence: 99%

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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“…This unique feature can be potentially used in a wide range of applications. Examples include security examination [3], throughwall monitoring [4][5][6][7][8], and medical imaging [9][10][11]. As an important research area, it has attracted much interest in microwave engineering and remote sensing.…”

Section: Introductionmentioning

confidence: 99%

Towards real‐time through‐obstacle imaging based on compressed sensing for sparse objects

Zhou

Shen

Meng

et al. 2019

IET Microwaves, Antennas & Propagation

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Although significant progress has been made in microwave imaging, real‐time imaging, especially for objects behind walls or closed obstacles, remains a technical challenge. In this work, highly efficient imaging for complex‐structured objects surrounded by a closed obstacle was experimentally demonstrated. The imaging equations are derived based on a combination of the inverse‐scattering problem and the concept of compressed sensing. Making use of the spatial sparsity of objects and obstacles, the compressed imaging can be implemented using a time‐division multi‐antenna setup with reduced transmitting antennas. Owing to the spatial compressed sensing applied to the sparse imaging region and objects, the imaging time can be reduced by two orders of magnitude compared with the conventional twofold subspace‐based optimisation method with a comparable imaging quality. Taking advantage of the sparsity of the entire imaging area, objects with larger relative permittivity can also be reconstructed. The proposed method can be potentially used in applications such as security examination through boxes. It also provides a new clue for solving the practicability difficulty faced by existing microwave imaging systems.

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A Rapid Medical Microwave Tomography Based on Partial Differential Equations

Cited by 24 publications

References 20 publications

An Overview of Microwave Imaging for Breast Tumor Detection

An Overview of Microwave Imaging for Breast Tumor Detection

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

Towards real‐time through‐obstacle imaging based on compressed sensing for sparse objects

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