Monostatic Radar-Based Microwave Imaging of Breast Tumor Using an Ultra-wideband Dielectric Resonator Antenna (DRA) with a Sierpinski Fractal Defected Ground Structure

Kaur, Gagandeep; Kaur, Amanpreet

doi:10.1007/s12647-022-00536-7

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…Rebuilding an image takes less than 6 s using the author-proposed forward solver and the nodal adjoint method for calculating the Jacobian matrix. Kaur et al 88 proposed a monostatic RBMWI system using a rectangular dielectric resonator antenna (DRA) with a Sierpinski fractal-defected ground structure, which has been simulated and experimentally tested for ultrawideband (UWB) operation to detect breast tumors. High-peak gain fractal DRA covers UWB ranging from 5.6 to 14.2 GHz, having 5.8 dB gain.…”

Section: State Of Art Mwi Techniques For Disease Detectionmentioning

confidence: 99%

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Khalid,

Zubair,

Mehmood

et al. 2024

npj Imaging

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In recent years, microwave imaging (MWI) has emerged as a non-ionizing and cost-effective modality in healthcare, specifically within medical imaging. Concurrently, advances in artificial intelligence (AI) have significantly augmented the capabilities of medical imaging tools. This paper explores the intersection of these two domains, focusing on the integration of AI algorithms into MWI techniques to elevate accuracy and overall performance. Within the scope of existing literature, representative prior works are compared concerning the application of AI in both the “MWI for Healthcare Applications" and “Artificial Intelligence Assistance In MWI" sections. This comparative analysis sheds light on the diverse approaches employed to enhance the synergy between AI and MWI. While highlighting the state-of-the-art technology in MWI and its historical context, this paper delves into the historical taxonomy of AI-assisted MWI, elucidating the evolution of intelligent systems within this domain. Moreover, it critically examines prominent works, providing a nuanced understanding of the advancements and challenges encountered. Addressing the limitations and challenges inherent in developing AI-assisted MWI systems like Generalization to different conditions, Generalization to different conditions, etc the paper offers a brief synopsis of these obstacles, emphasizing the importance of overcoming them for robust and reliable results in actual clinical environments. Finally, the paper not only underscores the current advancements but also anticipates future innovations and developments in utilizing AI for MWI applications in healthcare.

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Section: State Of Art Mwi Techniques For Disease Detectionmentioning

confidence: 99%

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Khalid,

Zubair,

Mehmood

et al. 2024

npj Imaging

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show abstract

“…The work done is compared to some of the recent works [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] in literature which is listed in Table 2. It can be observed that in the proposed work, the single tumor in the homogeneous breast phantom and two tumors in the heterogeneous breast phantom are detected clearly.…”

Section: Image Reconstruction Proceduresmentioning

confidence: 99%

Systematic Performance Evaluation for the Detection of Breast Tumors with Sinusoidal Corrugated Antipodal Vivaldi Antennas Utilizing DAS and It-DAS Methodologies

Asok,

Tripathi,

Dey

2023

PIER C

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This work presents a study where a Sinusoidal Corrugated Antipodal Vivaldi Antenna (SC-AVA) operating in the Ultra-Wideband (UWB) region is employed as a transducer for microwave imaging of a cancerous breast. The functionality of the antenna within the UWB range is initially confirmed through thorough testing of performance parameters, including return loss, gain, radiation pattern, and group delay. Subsequently, its practical application in biomedical imaging is evaluated by measuring Specific Absorption Rate (SAR) readings at multiple frequencies within the operational range. The SAR readings are obtained from an EM simulator by modelling both homogeneous and heterogeneous breast phantoms and placing them in close proximity to the transducer. The SAR values are recorded at various frequencies, and it is determined that these readings comply with the Federal Communication Commission (FCC) regulations. The modelled SC-AVA is further utilized in the detection of a single tumor in a homogeneous breast phantom and multiple tumors in a realistic heterogeneous breast phantom. These phantoms are developed in a laboratory environment and imaged using an in-house developed monostatic microwave imaging setup. To gather preliminary information about the target, a homogeneous phantom with one tumor is imaged initially. Subsequently the heterogeneous phantom with two embedded tumors is imaged in this study. The imaging results demonstrate that tumors of different sizes can be clearly visualized in both breast phantoms using the SC-AVA, employing image reconstruction algorithms such as Delay and Sum (DAS) and iterative Delay and Sum (it-DAS). Furthermore, a comparison of the reconstructed images reveals that the it-DAS reconstruction algorithm produces images with improved clarity compared to the DAS algorithm.

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“…Researchers have proposed different antennas and techniques to improve the accuracy and effectiveness of MSRMI for skin cancer detection and diagnosis. The different types of antennas that are utilized for this purpose are slot microstrip antennas, horn antennas, Vivaldi antennas, dielectric resonator antennas (DRA), bi‐conical, log periodic antennas, bow tie antennas, AMC integrated antennas, etc 7–13 . The antennas already avalilable in the literature have a large profile, low gain, low directivity, low efficiency, offer a wide band of operation, and are also complex to integrate within the MSRMI system.…”

Section: Introductionmentioning

confidence: 99%

“…The different types of antennas that are utilized for this purpose are slot microstrip antennas, horn antennas, Vivaldi antennas, dielectric resonator antennas (DRA), bi-conical, log periodic antennas, bow tie antennas, AMC integrated antennas, etc. [7][8][9][10][11][12][13] The antennas already avalilable in the literature have a large profile, low gain, low directivity, low efficiency, offer a wide band of operation, and are also complex to integrate within the MSRMI system. Thus, to overcome the drawbacks of the mentioned antennas for MI purposes, this research work proposes an Ultra Wide Band Archimedean spiral microstrip-patch antenna (UWB ASMA) for MSRMI of the human forearm to detect skin cancer and localize its position by creating a dielectric profile of the skin area under scan.…”

mentioning

confidence: 99%

In silico, in vitro, and in vivo validation of a microwave imaging system using a low‐profile Ultra Wide Band Archimedean spiral antenna to detect skin cancer

Kaur,

Kaur

2024

Int J Imaging Syst Tech

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Microwave imaging (MI) is a noninvasive and nonionizing procedure for detection of cancerous cells in healthy body tissues using radiofrequency (RF) and microwaves. The procedure involves the use of Ultra Wide Band (UWB) antennas for sensing purposes. Therefore, this research article presents the design, development, and testing of a low‐profile UWB Archimedean spiral microstrip‐patch antenna (ASMA) for detection of skin cancer using monostatic radar‐based microwave imaging. The proposed ASMA consists of a spiral resonator with a defective ground structure and a slotted microstrip feed line with dimensions of 38 × 38 × 0.87 mm3. The proposed antenna shows an impedance bandwidth for the frequency range of 2.2–13.9 GHz, with a peak gain of 6.8 dB at 7.8 GHz. In silico analysis of the proposed ASMA for MI is carried out with Gaustav model using Computer Simulation Technology Microwave Studio. To validate the performance of the ASMA as a sensor for MI, a prototype of the same is fabricated and a four‐layered bio‐phantom of the human forearm is prepared for in vitro and in vivo testing of the proposed procedure. The validation of ASMA radiation properties is done using a Vector Network Analyser (E‐5063A) (VNA) and an anechoic chamber with the fabricated antenna at 10 mm away from the prepared bio‐phantom. The recorded S parameter data with bio‐phantom and the VNA is processed using different beamforming algorithms like Delay and Sum and Coherent Factor‐Delay Multiply and Sum (CF‐DMAS) to reconstruct the image of the scanned area. The reconstructed images are 97%–98% accurate. The proposed ASMA sensor is also safe for human exposure as it has a specific absorption rate of 0.0546 W/Kg at 5 GHz that complies with the safety guidelines of the Federal Communications Commission to minimize potential health risks associated with exposure to RF and microwave radiation.

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Monostatic Radar-Based Microwave Imaging of Breast Tumor Using an Ultra-wideband Dielectric Resonator Antenna (DRA) with a Sierpinski Fractal Defected Ground Structure

Cited by 7 publications

References 25 publications

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Systematic Performance Evaluation for the Detection of Breast Tumors with Sinusoidal Corrugated Antipodal Vivaldi Antennas Utilizing DAS and It-DAS Methodologies

In silico, in vitro, and in vivo validation of a microwave imaging system using a low‐profile Ultra Wide Band Archimedean spiral antenna to detect skin cancer

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