Robust Breast Cancer Imaging Based on a Hybrid Artifact Suppression Method for Early-Stage Tumor Detection

Mehdi Mehranpour, Saughar Jarchi, Asghar Keshtkar, Ayaz Ghorbani, Ali Araghi, Mohsen Khalily, Okan Yurduseven

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Abstract

A high-resolution conformal array for detection of small size tumors inside the breast is proposed. The array consists of a novel cavity-backed low-profile aperture-stacked-patch (LP-ASP) antennas. The proposed antenna operates from 2.2 GHz to 13.5 GHz which enables the imaging system to be exploited across a high fractional bandwidth of approximately 149%. Thanks to the wide operating bandwidth of the designed antenna, the proposed system is not only applicable for a deep penetration imaging, but also for high resolution and accurate images acquisition. The proposed single element antenna has a compact size of 10 × 10 × 10.495 mm3 . So, it is possible to form a conformal array around the breast by applying numbers of the designed elements. Moreover, a Hybrid Artifact Suppression (HAS) method is presented to remove the artifact effects including skin reflection and mutual coupling between the elements. In this method, the artifact response of each channel is estimated using Independent Component Analysis (ICA) at the early-stage of the recorded signals. Additionally, in order to suppress the artifact data to accurately detect the malignant tumor, a Wiener filter is applied. To validate the practicality of the presented calibration algorithm in the proposed conformal array, the detection of a single spherical tumor (with a small diameter of 5 mm) within a realistic breast model in different scenarios is studied. Investigating of simulated and measured results of the designed antenna, and comparing quantitative metrics of successfully reconstructed tumor images by the proposed HAS and conventional calibration methods show the proposed system can be a good candidate for the breast cancer detection applications.
Original languageEnglish
Number of pages17
JournalIEEE Access
Early online date16 Nov 2020
DOIs
Publication statusEarly online date - 16 Nov 2020

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