A Prototype System for Measuring Microwave Frequency Reflections from the Breast

Bourqui, Jeremie; Sill, J.M.; Fear, Elise C.

doi:10.1155/2012/851234

Cited by 104 publications

(90 citation statements)

References 17 publications

(19 reference statements)

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“…Comparison of simulations and measurements demonstrates good agreement, particularly between the dominant reflections [4]. Finally, simulations are performed with and without the inclusion present in the model in order to permit isolation of the response from this object.…”

Section: Breast Modelmentioning

confidence: 77%

“…In the system under development at the University of Calgary [4], the woman lies prone with the breast extending into a tank of immersion liquid. At a selected elevation (z = constant), a single antenna is scanned around the breast model (i.e., in the x-y plane).…”

Section: Modelsmentioning

confidence: 99%

“…A prototype microwave imaging system has been developed for monostatic, radar-based data collection at the University of Calgary [4]. The prototype is called the Tissue Sensing Adaptive Radar (TSAR) system.…”

Section: Prototype Systemmentioning

confidence: 99%

“…The simulations are described in detail in [4] and include key features such as the tank and the tank lid. The antenna in simulations is excited with the same differentiated Gaussian pulse as synthesized with measured data.…”

Section: Breast Modelmentioning

confidence: 99%

“…This technique involves illuminating the breast with a pulse that is short in time (ultra-wideband in frequency) using an appropriate antenna. In a monostatic system, the antenna is typically scanned around the breast, recording reflections at a number of physical locations [4,5]. At all antenna positions, a dominant reflection is received from the skin due to the differences in the properties of the skin compared to the interior and exterior of the breast.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Neighborhood-Based Algorithm to Facilitate the Reduction of Skin Reflections in Radar-Based Microwave Imaging

Maklad¹,

Curtis²,

Fear³

et al. 2012

PIER B

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Abstract-Radar-based microwave imaging is being investigated as a complementary diagnostic tool for breast cancer detection. One of the major challenges associated with radar-based breast imaging is the removal of the overwhelming reflection caused by the skin. This paper presents an algorithm that has been designed for realistic 3D scenarios. The algorithm is tested on a variety of realistic 3D numerical breast models, as well as measured data from a phantom and patient. In all cases, the reflections from the skin are significantly reduced, facilitating detection of known tumors.

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Section: Breast Modelmentioning

confidence: 77%

Section: Modelsmentioning

confidence: 99%

Section: Prototype Systemmentioning

confidence: 99%

Section: Breast Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Neighborhood-Based Algorithm to Facilitate the Reduction of Skin Reflections in Radar-Based Microwave Imaging

Maklad¹,

Curtis²,

Fear³

et al. 2012

PIER B

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Experimental Demonstration of In‐Place Calibration for Time Domain Microwave Imaging System

Kwon

Lee

2018

Radio Science

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In this study, the experimental demonstration of in‐place calibration was conducted using the developed time domain measurement system. Experiments were conducted using three calibration methods—in‐place calibration and two existing calibrations, that is, array rotation and differential calibration. The in‐place calibration uses dual receivers located at an equal distance from the transmitter. The received signals at the dual receivers contain similar unwanted signals, that is, the directly received signal and antenna coupling. In contrast to the simulations, the antennas are not perfectly matched and there might be unexpected environmental errors. Thus, we experimented with the developed experimental system to demonstrate the proposed method. The possible problems with low signal‐to‐noise ratio and clock jitter, which may exist in time domain systems, were rectified by averaging repeatedly measured signals. The tumor was successfully detected using the three calibration methods according to the experimental results. The cross correlation was calculated using the reconstructed image of the ideal differential calibration for a quantitative comparison between the existing rotation calibration and the proposed in‐place calibration. The mean value of cross correlation between the in‐place calibration and ideal differential calibration was 0.80, and the mean value of cross correlation of the rotation calibration was 0.55. Furthermore, the results of simulation were compared with the experimental results to verify the in‐place calibration method. A quantitative analysis was also performed, and the experimental results show a tendency similar to the simulation.

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Classification of breast tumor models with a prototype microwave imaging system

et al. 2020

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Purpose: The assessment of the size and shape of breast tumors is of utter importance to the correct diagnosis and staging of breast cancer. In this paper, we classify breast tumor models of varying sizes and shapes using signals collected with a monostatic ultra-wideband radar microwave imaging prototype system with machine learning algorithms specifically tailored to the collected data. Methods: A database comprising 13 benign and 13 malignant tumor models with sizes between 13 and 40 mm was created using dielectrically representative tissue mimicking materials. These tumor models were placed inside two breast phantoms: a homogeneous breast phantom and a breast phantom with clusters of fibroglandular mimicking tissue, accounting for breast heterogeneity. The breast phantoms with tumors were imaged with a monostatic microwave imaging prototype system, over a 1-6 GHz frequency range. The classification of benign and malignant tumors embedded in the two breast phantoms was completed, and tumor classification was evaluated with Principal Component Analysis as a feature extraction method, and tuned Na€ ıve Bayes (NB), decision trees (DT), and knearest neighbours (kNN) as classifiers. We further study which antenna positions are better placed to classify tumors, discuss the feature extraction method and optimize classification algorithms, by tuning their hyperparameters, to improve sensitivity, specificity and the receiver operating characteristic curve, while ensuring maximum generalization and avoiding overfitting and data contamination. We also added a realistic synthetic skin response to the collected signals and examined its global effect on classification of benign vs malignant tumors. Results: In terms of global classification performance, kNN outperformed DT and NB machine learning classifiers, achieving a classification accuracy of 96.2% when classifying between benign and malignant tumor phantoms in a homogeneous breast phantom (both when the skin artifact is and is not considered). Conclusions:We experimentally classified tumor models as benign or malignant with a microwave imaging system, and we showed a methodology that can potentially assess the shape of breast tumors, which will give further insight into the correct diagnosis and staging of breast cancer.

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A Prototype System for Measuring Microwave Frequency Reflections from the Breast

Cited by 104 publications

References 17 publications

Neighborhood-Based Algorithm to Facilitate the Reduction of Skin Reflections in Radar-Based Microwave Imaging

Neighborhood-Based Algorithm to Facilitate the Reduction of Skin Reflections in Radar-Based Microwave Imaging

Experimental Demonstration of In‐Place Calibration for Time Domain Microwave Imaging System

Classification of breast tumor models with a prototype microwave imaging system

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