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Tumor Detection in Multilayer Brain Phantom Model by Symmetrical-Shaped DGS Rectangular Microstrip Patch Antenna

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International Conference on Intelligent Computing and Smart Communication 2019

Abstract

Rectangular microstrip patch antenna is designed for cancer tumor detection in the multilayer brain phantom model. Computer simulation technology-Microwave Studio (CST-MWS) is used to designed and simulated a multilayer brain phantom model with five layers and proposed. Spherical-shaped tumor of radius 05 mm has been designed inside the multilayer brain phantom model. The microwave signal is transmitted into the brain by RMPA (Rectangular Microstrip patch Antenna) and reflected signal from the brain phantom model with and without tumor has been analyzed based on their performance parameter to detect the tumor. Multilayer brain phantom model without tumor is interfaced with ultra-wideband RMPA and reflected signal shows the reflection coefficient at two frequencies, i.e., 28.59 dB at 6.42 GHz and 41.22 dB at 7.69 GHz. The current density of the model without tumor and ultra-wideband RMPA is 2706 A/m2. The specific absorption rate of the model without tumor is 4.511e+06 W/m3. Now the multilayer brain phantom model with the tumor is interfaced with ultra-wideband RMPA and reflected signal from the brain shows the reflection coefficient at two frequencies 29.19 dB at 6.42 GHz and 44.42 dB at 7.68 GHz. The current density of the model has been observed with tumor and found to be 2758 A/m2 and the corresponding absorption rate is found to be 8.523e+06 W/m3. It is concluded that the increased value of current density and SAR and the declined value of the return loss with the proposed model detects the cancerous tumor.

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Correspondence to Hemant Kumar Gupta .

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Gupta, H.K., Sharma, R., Thakre, V.V. (2020). Tumor Detection in Multilayer Brain Phantom Model by Symmetrical-Shaped DGS Rectangular Microstrip Patch Antenna. In: Singh Tomar, G., Chaudhari, N.S., Barbosa, J.L.V., Aghwariya, M.K. (eds) International Conference on Intelligent Computing and Smart Communication 2019. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0633-8_71

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