{"title":"Exploring the structural features of Triangular fractal antenna for detection of brain tumor","authors":"P. Bini Palas, K. Rahimunnisa","doi":"10.1016/j.asej.2025.103369","DOIUrl":null,"url":null,"abstract":"<div><div>Fractal antennas are being more widely employed in medical imaging, notably microwave imaging for brain tumour detection. The characteristics they possess make them an excellent choice for identifying tumours of varying sizes and depths. This article introduces an innovative Sierpinski Trio fractal antenna (STFA) designed for the detection of brain tumours and showcases improved antenna performance metrics. The STFA has been designed using the CST simulation tool, achieving a maximum return loss of −77.38 dB, a gain of 14.13 dBi, and a directivity of 15.73 dB at a frequency of 4.72 GHz. In addition to the fractal antenna construction, the simulation tool is used to build the five-layered head phantom. Parametric research was conducted to optimise the embedded structure of the STFA and head phantom for diverse tumour sizes, and the antenna performances were examined. The STFA structure detects tumour sizes ranging from 5 to 20 mm and delivers return loss of −57.28 dB, −45.23 dB, −51.62 dB, and −47.59 dB. The suggested antenna has applications in the medical field, particularly in the detection of kidney stones, breast tumours, and tumour cells in the human brain.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 5","pages":"Article 103369"},"PeriodicalIF":6.0000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ain Shams Engineering Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2090447925001108","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Fractal antennas are being more widely employed in medical imaging, notably microwave imaging for brain tumour detection. The characteristics they possess make them an excellent choice for identifying tumours of varying sizes and depths. This article introduces an innovative Sierpinski Trio fractal antenna (STFA) designed for the detection of brain tumours and showcases improved antenna performance metrics. The STFA has been designed using the CST simulation tool, achieving a maximum return loss of −77.38 dB, a gain of 14.13 dBi, and a directivity of 15.73 dB at a frequency of 4.72 GHz. In addition to the fractal antenna construction, the simulation tool is used to build the five-layered head phantom. Parametric research was conducted to optimise the embedded structure of the STFA and head phantom for diverse tumour sizes, and the antenna performances were examined. The STFA structure detects tumour sizes ranging from 5 to 20 mm and delivers return loss of −57.28 dB, −45.23 dB, −51.62 dB, and −47.59 dB. The suggested antenna has applications in the medical field, particularly in the detection of kidney stones, breast tumours, and tumour cells in the human brain.
期刊介绍:
in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance.
Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.