Breast Imaging Using Microwave Tomography With Radar-Based Tissue-Regions Estimation

Baran, Anastasia; Kurrant, Douglas; Zakaria, Amer; Fear, Elise C.; LoVetri, Joe

doi:10.2528/pier14080606

Cited by 56 publications

(38 citation statements)

References 16 publications

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“…Nevertheless, recent studies have shown that when BMR is used in conjunction with microwave tomography, it can improve the accuracy of the diagnosis. 36 Another option that has been recently proposed is the use of contrast agents. In the last two years, the use of nontoxic compounds such as nanoparticles and free radicals have, in simulated datasets, shown promising results for enhancing the contrast between fibroglandular and malignant breast tissues.…”

Section: Discussionmentioning

confidence: 99%

Experimental feasibility of multistatic holography for breast microwave radar image reconstruction

et al. 2016

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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.

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Section: Discussionmentioning

confidence: 99%

Experimental feasibility of multistatic holography for breast microwave radar image reconstruction

et al. 2016

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“…Traditional reconstruction techniques such as filtered backpropagation (FBPP) [26] and Fourier inversion use this projection data from [0, 2π] angular coverage for accurate image recovery. Though the formulation applies to weak scatterers, it is widely used and since its introduction, a steady research focus has been maintained on this topic [27][28][29][30][31][32][33]. Present day research on DT focuses on image recovery from projection data obtained under constraints of angular coverage and/or the number of available projections.…”

Section: Diffraction Tomographymentioning

confidence: 99%

Image Reconstruction From Highly Sparse and Limited Angular Diffraction Tomography Using Compressed Sensing Approach

Paladhi

Tayebi

Banerjee

et al. 2017

PIER

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Abstract-Diffraction tomography (DT) from limited projection data has been an active research topic for over three decades. The interest has been steadily fueled due to its application in multiple disciplines including medical imaging, structural health monitoring and non-destructive evaluation to name a few. This paper explores the applicability of compressed sensing to recover complex-valued objective functions (e.g., complex permittivity in microwave tomography). Generally, compressed sensing based tomographic reconstruction has been studied under full angular access. In this paper, the effect of lowering the angular access in addition to highly limited number of projection data is explored. The effectiveness of the reconstruction methods is tested with severely limited dataset which would render reconstruction impossible by traditional iterative approximation methods. Furthermore, results show that complex-valued phantoms can be reconstructed from as few as 15 projections from 120 • coverage, a significant finding. In this study, the Total Variation (TV) has been used as the l 1 norm within the compressed sensing framework. The robustness of the algorithm in presence of noise is discussed. Use of multiple sparse domains has also been explored briefly. The results show the effectiveness of TV as a regularization parameter even for complex-valued images under the compressed sensing regime. This is a pertinent observation as TV is a simple norm to implement. For a large class of images, especially in medical imaging, this implies the availability of a steady l 1 norm for easy implementation of compressed sensing reconstruction for complex-valued images.

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“…The scheme is applicable to microwave tomography of tissue samples. It has been of great interest in tomography of human breast to identify malignant tumours [8][9][10][11][12][13][14]. The high contrast between healthy and cancerous breast tissue provides opportunities for clearly identifying malignancies within breast tissue.…”

Section: Introductionmentioning

confidence: 99%

“…Faster implementations for backprojections algorithms are also being intensely explored, e.g., [17]. Again, radar based methods have been combined with microwave tomography to generate higher resolutions for medical imaging [10]. Thus, any improvement in the traditional backpropagation techniques is of potential interest across multiple disciplines.…”

Section: Introductionmentioning

confidence: 99%

Improved Backpropagation Algorithms by Exploiting Data Redundancy in Limited-Angle Diffraction Tomography

Paladhi

Sinha²,

Tayebi

et al. 2016

PIER B

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Filtered backpropagation (FBPP) is a well-known technique used in Diffraction Tomography (DT). For accurate reconstruction of a complex-valued image using FBPP, full 360 • angular coverage is necessary. However, it has been shown that by exploiting inherent redundancies in the projection data, accurate reconstruction is possible with 270 • coverage. This is called the minimal-scan angle range. This is done by applying weighting functions (or filters) on projection data of the object to eliminate the redundancies. There could be many general weight functions. These are all equivalent at 270 • coverage but would perform differently at lower angular coverages and in presence of noise. This paper presents a generalized mathematical framework to generate weight functions for exploiting data redundancy. Further, a comparative analysis of different filters when angular coverage is lower than minimal-scan angle of 270 • is presented. Simulation studies have been done to find optimum weight filters for sub-minimal angular coverage. The optimum weights generate images comparable to a full 360 • coverage FBPP reconstruction. Performance of the filters in the presence of noise is also analyzed. These fast and deterministic algorithms are capable of correctly reconstructing complex valued images even at angular coverage of 200 • while still under the FBPP regime.

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Breast Imaging Using Microwave Tomography With Radar-Based Tissue-Regions Estimation

Cited by 56 publications

References 16 publications

Experimental feasibility of multistatic holography for breast microwave radar image reconstruction

Experimental feasibility of multistatic holography for breast microwave radar image reconstruction

Image Reconstruction From Highly Sparse and Limited Angular Diffraction Tomography Using Compressed Sensing Approach

Improved Backpropagation Algorithms by Exploiting Data Redundancy in Limited-Angle Diffraction Tomography

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