Wide-band Meta-surface Antenna for Microwave Brain Imaging systems

Salimitorkamani, Mahdi; Odabasi, Hayrettin; Turan, Goksel

doi:10.23919/ursigass51995.2021.9560498

Cited by 3 publications

(3 citation statements)

References 12 publications

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“…Besides, the detection cost is low, and the detection speed is fast. So, the microwave detection system is expected to become a new generation of equipment to detect strokes for public [4], [5]. Microwave tomography technology is a kind of non-destructive testing.…”

Section: ) (Corresponding Author: Ming Yu)mentioning

confidence: 99%

Classification and Location of Cerebral Hemorrhage Points Based on SEM and SSA-GA-BP Neural Network

Li,

Wang,

et al. 2024

IEEE Trans. Instrum. Meas.

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In this paper, a method to fast classify (Intradural hemorrhage, epidural hemorrhage, and cerebral parenchymal hemorrhage) and locate the bleeding points by using the Singularity Expansion Method (SEM) and Backpropagation (BP) neural network optimized by genetic algorithm (GA) and Sparrow Search Algorithm (SSA) is proposed. In the simulation model, the bleeding spot with a radius of 3 mm is successfully identified by the approach. The test accuracy in the simulation for both the bleeding's localization and classification are 98.0% and 97.4%, respectively. Head phantoms that have all been improved over the previous phantom established are used for experiments. A bleeding target with a volume of 3 ml can be identified in the microwave detection system. In the experiment, the accuracy of classification and localization of the bleeding type are 90% and 94.7%, respectively. The final results demonstrate the capability and effectiveness of the method. Faster determination of bleeding point type and orientation means that patients can be provided with different rescue measures accordingly.

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Section: ) (Corresponding Author: Ming Yu)mentioning

confidence: 99%

Classification and Location of Cerebral Hemorrhage Points Based on SEM and SSA-GA-BP Neural Network

Li,

Wang,

et al. 2024

IEEE Trans. Instrum. Meas.

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“…4 In recent years, numerous MWI systems and antennas have been proposed in the literature for brain imaging purposes. [5][6][7][8][9] These systems differentiate between healthy and unhealthy brain tissues based on the contrast in dielectric properties. As blood primarily consists of water, it displays higher dielectric properties compared to most brain tissues, excluding the CSF.…”

Section: Introductionmentioning

confidence: 99%

“…Microwave imaging (MWI) systems have emerged as a promising technology for various applications, including medical imaging 3 and security screening 4 . In recent years, numerous MWI systems and antennas have been proposed in the literature for brain imaging purposes 5–9 . These systems differentiate between healthy and unhealthy brain tissues based on the contrast in dielectric properties.…”

Section: Introductionmentioning

confidence: 99%

A low‐cost and multifunctional long‐life anthropomorphic head phantom for microwave brain imaging systems

Salimitorkamani,

Mehranpour,

Cansiz

et al. 2024

Micro & Optical Tech Letters

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To assess the performance of microwave brain imaging (MWBI) systems, an anthropomorphic multifunctional head phantom with long life, low cost, and reliable dielectric properties over the intended frequency range is a principal requisite. A solid head model has been developed using a mold casting method, incorporating graphite, aluminum oxide, carbon black powder, and brass powder with epoxy/hardener. Four healthy solid brain tissues consisting of skin, skull, gray matter, and white matter are fabricated to mimic realistic head tissue properties along with cerebrospinal fluid. The constructed head model incorporates four cavities of varying sizes and positions, designed to accommodate healthy or unhealthy cores, thereby simulating diverse stroke scenarios without necessitating separate healthy and unhealthy models. Utilizing a single‐head model preserves dielectric properties during comparative analysis (healthy/unhealthy), except for core components. Tissue properties were measured twice, three months apart, showing good agreement between theoretical and measured results.

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