This paper proposes a simple and computationally efficient algorithm for the detection and localization of early tumors (<5 mm) in the breast tissues. The feasibility of the proposed technique is demonstrated with three-dimensional EM simulators and validated with experimental results on a breast phantom using wideband patch antenna operating in 2.4–4.7 GHz band. The proposed method identifies the tumor location and the depth of the tumor. This is accomplished by employing a mean value approach and an efficient algorithm. Average value of the backscattered signal received by the antenna at different location is considered in the mean value technique. The depth of tumor is identified by Ground Penetrating Radar algorithm which employs the backscattered signals from the breast tissues. These data are converted to B-scan image which in turn gives the depth of the tumor. The results obtained in the experiment are in congruence with the simulated results. In the experimental analysis, the tumor location is identified when the size of the tumor is large owing to the low sensitivity of the antenna.

This paper consists of a compact polarization-independent dual-band pass Frequency Selective Surface (FSS) for smart phone safety application. The FSS structure is entrenched in FR-4 substrate, which acts as a band pass filter for a frequency of 2.4 GHz and 5 GHz. These two pass band frequencies are independently controlled by tuning the unit cell geometrical parameters. The unit cell shows a symmetrical shape to enable constant performance in both TE and TM mode. By considering different angles (0°- 60°) for the incidence of waves and the angular stability is verified. The proposed unit cell structure is developed with the help of CST microwave studio. The performance of the proposed FSS were validated with the help of simulated and measured results. In reflection mode analysis, the specific frequency is passed and the remaining frequencies received at the receiving end are attenuated near to 30 dB. The accurate results are obtained at 2.25 GHz and 4.77 GHz.

Background: Universally, the most predominant cause of female mortality is mainly due to breast cancer. Owing to numerous constraints in the existing imaging technique, researchers are trying out an alternative tool to detect the tumor before going to the miserable stage. Methods: This article presents a novel method to detect the mean value system for detecting the location of the tumor in different depths by shifting the antenna anywhere in the breast tissue. In addition, an algorithm to reconstruct the breast image, namely Delay-Multiply-and-Sum (DMAS) is followed to identify the tumor implanted in the breast tissue. Results: The analysis shows that the maximum mean value occurs while the antenna moves very near to the tumor while the mean value reduces while the antenna shifts apart from the tumor location. The mean value in different locations is converted into a microwave image. The high intensity in the image exhibits the precise position of the tumor. This technique can identify the location of early-stage tumor of size 3mm. Multiple tumors of sizes 6mm and 7mm can identify at a depth of 12mm and 18mm in the homogeneous breast phantom. DMAS can provide better imaging results in the early stage tumor of size 3mm embedded in the breast phantom. Conclusion: Microwave imaging is an efficient technique to differentiate healthy and malignant tissue in the breast. Antenna plays a major role in identifying tumors in the breast in the early stage. Hence a high-performance Ultra Wideband Dielectric Resonator Antenna (DRA-UWB) is used to identify the tumor in the breast. An antenna is sketched in different locations of the breast phantom. On account of the hemispherical structure, the mean value of the reflected signal is high at the center than at the edge. Hence, the difference in mean value is calculated with and without breast phantom for identifying the tumor location. The overall efficiency of this technique can be improved by using a high-performance UWB antenna. The image of the breast is reformed by the DMAS beamforming algorithm.