用于非侵入式脑细胞探测的低成本贴片天线

Abdullah Alzahrani
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引用次数: 0

摘要

癌症是全世界最常见的死亡原因之一。脑肿瘤是一种严重而危险的类型,其检测技术存在一些困难;当肿瘤较小时,很难在早期确定其位置。这项工作的目的是设计一种适用于检测脑癌肿瘤的低成本微带贴片天线传感器。利用计算机仿真技术 CST Studio Suite 三维电磁仿真和分析,设计了一个频率分别为 2.8GHz、3.9GHz、5GHz 和 5.6GHz 的贴片天线,用于诊断脑肿瘤。这些共振频率(低频段(L-B)2 GHz、中频段(M-B)3.9-5 GHz 和高频段(U-B)> 5 GHz)之间的比较研究是通过脂肪、硬脑膜、大脑、皮肤、CSF(脑脊液)和头骨六层大脑模型进行的。设计的贴片传感器在脑模型上没有肿瘤细胞和有肿瘤细胞的两种情况下都进行了评估。观察到了三个参数,即频率相移、深度反射回波损耗和功率吸收,用于指示肿瘤细胞的存在。这项研究得出结论,中波段(M-B)具有良好的穿透性和较好的回波损耗深度,约为 -20dB。同时,高频段具有 21 MHz 相移的高分辨率,但回波损耗差深度值仅为-0.1dB。所提出的工作可为生物医学应用中的贴片传感器设计提供一条途径。
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A Low-Cost Patch-Antenna for Non-Invasive Brain Cell Detection
Cancer is one of the most and frequent causes of death around the world. Brain tumor is a critical and dangerous type and has a few difficulties of the techniques used for its detection; it is hard to determine its location when it is small at an early stage. The purpose of this work is to design a patch antenna sensor that is a low-cost microstrip which is suitable to detect a brain cancer tumor. The computer simulation technology CST Studio Suite 3D EM simulation and analysis was used to design a patch antenna with different frequencies of 2.8 GHz, 3.9 GHz, 5GHz and 5.6GHz to diagnose brain tumors. A comparison study between these resonance frequencies (lower-band (L-B) 2 GHz, middle-band (M-B) 3.9-5 GHz and upper-band (U-B) > 5 GHz) has been performed with six layers of brain phantom of fat, dura, brain, skin, CSF (Cerebrospinal Fluid) and skull. The designed patch sensor was assessed on both scenarios without and with a tumor cell on a brain phantom. Three parameters have been observed, the frequency phase shift, the deep amount of reflection return loss and power absorption were used to indicate the presence of the tumor cell. This study concludes that the middle-band (M-B) results in good penetration and better return loss depth around - 20dB. Meanwhile, the higher band provides high resolution of 21 MHz phase-shift but with only depth value of difference return loss of -0.1dB. The proposed work could provide a pathway on the design of patch sensors for biomedical applications.
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