Optimetric analysis of 1x4 array of circular microwave patch antennas for mammographic applications using adaptive gradient descent algorithm

Interest in the use of microwave equipment for breast imagery is on the increase owing to its safety, ease of use and friendlier cost. However, some of the pertinent blights of the design and optimization of microwave antenna include intensive consumption of computing resources, high price of software acquisition and very large optimization time. This paper therefore attempts to address these concerns by devising a rapid means of designing and optimizing the performance of a 1×4 array of circular microwave patch antenna for breast imagery applications by deploying the adaptive gradient descent algorithm (AGDA) for a circumspectly designed artificial neural network. In order to cross validate the findings of this work, the results obtained using the adaptive gradient descent algorithm was compared with those obtained with the deployment of the much reported Levenberg-Marquardt algorithm for the same dataset over same frequency range and training constraints. Analysis of the performance of the AGDA neural network shows that the approach is a viable and accurate technique for rapid design and analysis of arrays of circular microwave patch antenna for breast imaging

Optimetric analysis of 1x4 array of circular microwave patch antennas for mammographic applications using adaptive gradient descent algorithm

Interest in the use of microwave equipment for breast imagery is on the increase owing to its safety, ease of use and friendlier cost. However, some of the pertinent blights of the design and optimization of microwave antenna include intensive consumption of computing resources, high price of software acquisition and very large optimization time. This paper therefore attempts to address these concerns by devising a rapid means of designing and optimizing the performance of a 1×4 array of circular microwave patch antenna for breast imagery applications by deploying the adaptive gradient descent algorithm (AGDA) for a circumspectly designed artificial neural network. In order to cross validate the findings of this work, the results obtained using the adaptive gradient descent algorithm was compared with those obtained with the deployment of the much reported Levenberg-Marquardt algorithm for the same dataset over same frequency range and training constraints. Analysis of the performance of the AGDA neural network shows that the approach is a viable and accurate technique for rapid design and analysis of arrays of circular microwave patch antenna for breast imaging

A Meandered Line Patch Antenna at Low Frequency Range for Early Stage Breast Cancer Detection

Every year a concerning number of women are affected by breast cancer which is one of the deadliest and common types of cancers. Breast cancer is curable at early stages. For detecting breast cancer, there are several methods such as MRI, Mammography, Tomography, Ultrasound, and biopsy are available in medical technology. Still, none of them are as easy and efficient as a microwave imaging technique, in this method, the antenna plays an important role. Therefore, this paper focuses on developing an antenna at a low-frequency range for microwave imaging techniques to detect cancerous tissue inside the breast. For this, the antenna parameters, i.e., return loss, VSWR, directivity, current density, and specific absorption rate were studied, by setting the antenna over without tumor and with tumor breast as up-side-down, to ensure the compatibility of the antenna for the technique as well as for the patient’s body. A 5mm radius cancerous tumor was created inside the breast with dielectric conductivity of 4 and relative permittivity of 50. Cancerous cells were detected by reading the antenna parameters’ comparison between the healthy breast and the affected breast. The whole study was conducted by using CST MICROWAVE STUDIO SUITE 2020.

Terahertz Microstrip Patch Antenna for Breast Tumour Detection

Breast cancer is one of the most common cancers among Malaysian women. It is critical to discover strategies to detect the tumour early on. Terahertz (THz) frequency provides excellent qualities for detecting tumours such as low photon energy and non-ionising radiation as compared to prior methods such as mammography, ultrasound, and magnetic resonance imaging (MRI) that use optical to X-ray frequencies. The purpose of this work is to analyse and locate a breast tumour as well as to compute the maximum specific absorption rate (SAR) value. It was designed a THz rectangular microstrip patch antenna with an inset feed. To improve the antenna's performance, graphene was used for the patch and polyimide for the substrate. This antenna covered a bandwidth of 31.6 GHz and worked in the frequency range of 0.283-0.599 THz. To identify the location of a tumour, compute the SAR value, and localise the tumour, SAR simulation was used. The maximum SAR shifted to the tumor's position due to greater absorption rate around its tissue due to higher dielectric constant features. It was calculated that 1e-05g of average mass is required to be less than total tissue mass, which is 2.0063e-05g. SAR study revealed a maximum SAR value of 2.49391e+06 W/kg, which was not more than the overall absorption rate for human body safety. The SAR calculation result revealed that the tumour is within the range of the tumor's initial location

Determination of the breast cancer tumor diameter using a UWB microwave antenna system

This paper presents a novel ultra-wideband microwave antenna system to detect breast cancer and estimate tumor diameter. The system operates within the frequency range of 1 to 12 GHz and comprises a microstrip-fed monopole antenna that encircles the breast to identify the presence of tumors. The study demonstrates that a tumor within the breast can be detected by observing changes in the distribution of current density within the breast tissue, particularly in regions containing tumors of varying sizes. The research findings reveal that the system can identify breast tumors with the highest recorded current density of 188 A/m2 in cases with a tumor diameter of 30 mm, while the lowest recorded current density is 140 A/m2 for tumors with a diameter of 5 mm. Furthermore, the highest Specific Absorption Rate (SAR) value measured at the surface of the breast model is 0.2 W/kg. To determine the diameter of the tumors, the system collects and analyzes backscattered waves from a breast model. The investigation covers tumors with diameters ranging from 1 mm to 35 mm, and the received signals are recorded. In contrast to prior research, this study introduces an empirical model with a remarkable accuracy rate of 92.28% for characterizing the diameter of breast tumors based on the measurement analysis.</p