Development of Microwave Antenna for Cancer Treatment

Mustafa, Nurfarhana; Razak, Nur Hazimah Syazana Abdul; Yusof, Nurhafizah Abu Talip; Karim, Mohamad Shaiful Abdul

doi:10.1007/978-3-030-70917-4_14

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…This rise may be attributed to obesity, the spread of the Hepatitis C virus (HCV), and the increasing incidence of liver cancer [2]. Figures 2-5 illustrate the various stages of liver tumors, along with the corresponding diagnosis and treatment procedures required for each stage [3]. CT scanning has improved the detection of cancer, facilitated surgical procedures, enhanced radiation therapy, and advanced the monitoring of cardiac conditions, thereby eliminating the need for exploratory surgeries [4].…”

Section: Liver Tumors and Stagesmentioning

confidence: 99%

Experimental Investigations to Detection of Liver Cancer Using ResUNet

Kodepogu,

Muthineni,

Kethineedi

et al. 2023

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The detection and identification of cancerous tissue is currently a time-consuming and challenging process. The segmentation of liver lesions from cancer CT images can aid in treatment planning and clinical response monitoring. This study employs Residual U-Net, a powerful tool that has been adapted and applied for the segmentation of liver tumors, addressing the ongoing challenge in liver cancer diagnosis. Segmentation of liver lesions in CT images can be utilized to assess tumor burden, predict therapeutic outcomes, and monitor clinical response. In this research, the liver was extracted from the CT image using ResUNet, and the tumor was subsequently segmented using another ResUNet applied to the extracted Region of Interest (ROI). This approach effectively extracts features from Inception by combining residual and pre-trained weights. The deep learning system elucidates the underlying concept by highlighting the components contributing to the inner layer analysis and prediction, and by revealing a section of the decision-making process employed by pretrained deep neural networks.

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Section: Liver Tumors and Stagesmentioning

confidence: 99%

Experimental Investigations to Detection of Liver Cancer Using ResUNet

Kodepogu,

Muthineni,

Kethineedi

et al. 2023

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“…The microwave field has a wide range of applications in biomedical, such as thermotherapy by Mustafa et al, [1], laser ablation by Schena et al, [2], microwave imaging by Alsawaftah et al, [3], and photo-acoustic imaging by Fadhel et al, [4]. To create small, lightweight, and strong designs for microwave applications, materials with high permittivity are required [5].…”

Section: Introductionmentioning

confidence: 99%

Innovative and Cost-Effective Fabrication Technique for Dielectric Composite Material

Nurfarhana Mustafa,

Syamimi Mardiah Shaharum,

Ahmad Afif Mohd Faudzi

et al. 2024

ARAM

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In this paper, the fabrication process of epoxy resin and nanocomposite barium titanate using a cost-effective apparatus is presented along with measurements of complex permittivity. The material is prepared by mixing epoxy resin and barium titanate powder which has high permittivity. Measurement of complex permittivity of materials is performed using a waveguide technique in the G-band with a frequency between 4 and 6 GHz. The results are then compared with the previous works that use advanced and precision instrumentation. The results indicate that the material’s permittivity, determined using our proposed technique, performs admirably. Specifically, at a frequency of 5 GHz, the permittivity is 7.32 with a loss tangent of 0.025 for a filler concentration of 20%. These values not only meet but also closely match those obtained with high-end equipment. Therefore, the proposed technique could be a good potential as an alternative technique for dielectric material preparation which is suitable to be used as a substrate antenna.

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