453 research outputs found

    Empirical Assessment of Breast Lesion Detection Capability Through an Innovative Microwave Imaging Device

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    This paper investigates the effect of conductivity weighting on microwave images obtained through a dedicated imaging device. MammoWave is a microwave imaging device for detection of breast lesions, operating using only two azimuthally rotating antennas without the use of matching liquids. For each breast, a set of conductivity weighted images are generated through modifying our algorithm based on Huygens principle, producing intensity maps representing the homogeneity of tissues’ dielectric properties. Subsequently, we introduce several imaging parameters (i.e. features) to quantify the non-homogenous behaviour of the image. Through empirical investigation on 103 breasts, we can verify that a selection of these features could allow distinction between breasts with radiological findings (WF), i.e. with benign or malign lesions, and breasts with no radiological findings (NF). Statistical significance was set at p<0.05.We obtained single features Area Under the receiver operating characteristic Curves (AUCs) spanning from 0.65 to 0.68. Significantly, we achieve AUCs of up to 0.77 when considering dense breasts only, which tend to cause detection limitations in mammography exams

    A Microwave Imaging Procedure for Lung Lesion Detection: Preliminary Results on Multilayer Phantoms

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    In this work, a feasibility study for lung lesion detection through microwave imaging based on Huygens’ principle (HP) has been performed using multilayer oval shaped phantoms mimicking human torso having a cylindrically shaped inclusion simulating lung lesion. First, validation of the proposed imaging method has been performed through phantom experiments using a dedicated realistic human torso model inside an anechoic chamber, employing a frequency range of 1–5 GHz. Subsequently, the miniaturized torso phantom validation (using both single and double inclusion scenarios) has been accomplished using a microwave imaging (MWI) device, which operates in free space using two antennas in multi-bistatic configuration. The identification of the target’s presence in the lung layer has been achieved on the obtained images after applying both of the following artifact removal procedures: (i) the “rotation subtraction” method using two adjacent transmitting antenna positions, and (ii) the “ideal” artifact removal procedure utilizing the difference between received signals from unhealthy and healthy scenarios. In addition, a quantitative analysis of the obtained images was executed based on the definition of signal to clutter ratio (SCR). The obtained results verify that HP can be utilized successfully to discover the presence and location of the inclusion in the lung-mimicking phantom, achieving an SCR of 9.88 dB

    New Reconstructed Database for Cost Reduction in Indoor Fingerprinting Localization

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    Location fingerprinting is a technique widely suggested for challenging indoor positioning. Despite the significant benefits of this technique, it needs a considerable amount of time and energy to measure the Received Signal Strength (RSS) at Reference Points (RPs) and build a fingerprinting database to achieve an appropriate localization accuracy. Reducing the number of RPs can reduce this cost, but it noticeably degrades the accuracy of positioning. In order to alleviate this problem, this paper takes the interior architecture of the indoor area and signal propagation effects into account and proposes two novel recovery methods for creating the reconstructed database instead of the measured one. They only need a few numbers of RPs to reconstruct the database and even are able to produce a denser database. The first method is a new zone-based path-loss propagation model which employs fingerprints of different zones separately and the second one is a new interpolation method, zone-based Weighted Ring-based (WRB). The proposed methods are compared with the conventional path-loss model and six interpolation functions. Two different test environments along with a benchmarking testbed, and various RPs configurations are also utilized to verify the proposed recovery methods, based on the reconstruction errors and the localization accuracies they provide. The results indicate that by taking only 11% of the initial RPs, the new zone-based path-loss model decreases the localization error up to 26% compared to the conventional path-loss model and the proposed zone-based WRB method outperforms all the other interpolation methods and improves the accuracy by 40%

    Huygens principle based UWB microwave imaging method for skin cancer detection

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    In recent years, Ultra Wideband (UWB) technology has emerged as a promising alternative for use in a wide range of applications. One of the potential applications of UWB is in healthcare and imaging, motivated by its non-ionizing signals, low cost, low complexity, and its ability to penetrate through mediums. Moreover, the large bandwidth covered by UWB signals permits the very high resolution required in imaging experiments. In this paper, a recently introduced UWB microwave imaging technique based on the Huygens principle (HP), has been applied to multilayered skin model with an inclusion representing a tumor. The methodology of HP permits the capture of contrast such that different material properties within the region of interest can be discriminated in the final image, and its simplicity removes the need to solve inverse problems when forward propagating the waves. Therefore the procedure can identify and localize significant scatterers inside a multilayered volume. Validation of the technique through simulations on multilayered cylindrical model of the skin with inclusion representing the tumor has been performed

    Free space operating microwave imaging device for bone lesion detection: a phantom investigation

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    In this letter, a phantom validation of a low complexity microwave imaging device operating in free space in the 1-6.5 GHz frequency band is presented. The device, initially constructed for breast cancer detection, measures the scattered signals in a multi-bistatic fashion and employs an imaging procedure based on Huygens principle. Detection has been achieved in both bone fracture lesion and bone marrow lesion scenarios using the superimposition of five doublet transmitting positions, after applying the rotation subtraction artefact removal method. A resolution of 5 mm and a signal to clutter ratio (3.35 in linear scale) are achieved confirming the advantage of employing multiple transmitting positions on increased detection capability

    Dataset related to "A multicentric, single arm, prospective, stratified clinical investigation to evaluate MammoWave’s ability in breast lesions detection"

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    Microwave imaging is a safe and promising new technology in breast radiology, avoiding discomfort of breast compression and usage of ionizing radiation. This dataset relates to a paper which presents the first prospective microwave breast imaging study during which both symptomatic and asymptomatic subjects were recruited. Specifically, a prospective multicentre international clinical trial was performed in 2020-2021, to investigate the capability of a microwave imaging device (MammoWave) in allowing distinction between breasts with no radiological finding (NF) and breasts with radiological findings (WF), i.e., with benign or malignant lesions. Each breast scan was performed with the volunteers lying on a dedicated examination table in a comfortable prone position. MammoWave output was compared to reference standard (i.e., radiologic study obtained within the last month and integrated with histological one if available and deemed necessary by responsible investigator) to classify breasts into NF/WF categories. MammoWave output consists of a selection of microwave images’ features (determined prior to trials’ start), which allow distinction between NF and WF breasts (using statistical significance p<0.05). 353 women were enrolled in the study (mean age 51 years ± 12 [SD], minimum age 19, maximum age 78); MammoWave data from the first 15 women of each site, all with NF breasts, were used for calibration. Following central assessor evaluation, 111 NF (48 dense) and 272 WF (136 dense) breasts were used for comparison with MammoWave output. 272 WF comprised 182 benign findings and 90 malignant histology-confirmed cancer. A sensitivity of 82.3% was achieved (95%CI: 0.78-0.87); sensitivity is maintained when limiting the investigation to histology-confirmed breasts cancer only (90 histology-confirmed breasts cancer have been included in this analysis, having sizes ranging from 3 mm to 60 mm). Specificity value of approximately 50% was achieved as expected, since thresholds were calculated (for each feature) using median value obtained after recruiting the first 15 women (of each site), all NF. This prospective trial may represent another step for introducing microwave imaging into clinical practice, for helping in breast lesion identification in asymptomatic women

    UWB device for breast microwave imaging: phantom and clinical validations

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    Microwave imaging has received increasing attention in the last decades, motivated by its application in diagnostic imaging. Such effort has been encouraged by the fact that, at microwave frequencies, it is possible to distinguish between tissues with different dielectric properties. In such framework, a novel microwave device is presented here. The apparatus, consisting of two antennas operating in air, is completely safe and non-invasive since it does not emit any ionizing radiation and it can be used for breast lesion detection without requiring any breast crushing. We use Huygens Principle to provide a novel understanding into microwave imaging; specifically, the algorithm based on this principle provides images which represent homogeneity maps of the dielectric properties (dielectric constant and/or conductivity). The experimental results on phantoms having inclusions with different dielectric constants are presented here. In addition, the capability of the device to detect breast lesions has been verified through clinical examinations on 51 breasts. We introduce a metric to measure the non-homogeneous behaviour of the image, establishing a modality to detect the presence of inclusions inside phantoms and, similarly, the presence of a lesion inside a breast
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