Detection of haemorrhagic stroke in simulation and realistic 3-D human head phantom using microwave imaging

Sohani, Behnaz; Khalesi, Banafsheh; Ghavami, Navid; Ghavami, Mohammad; Dudley, Sandra; Rahmani, Amir; Tiberi, Gianluigi

doi:10.1016/j.bspc.2020.102001

Cited by 43 publications

(21 citation statements)

References 23 publications

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“…Our previous work in [ 12 ] has confirmed that the HP based procedure permits detection (in an anechoic chamber) of strong scatterers and can distinguish between different tissues in the final image. Following on from this initial exposition, there is a medical requirement for a portable brain stroke imaging device.…”

Section: Discussionmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

“…In response to the mentioned limitations of MWT systems and the medical necessities of brain stroke detection, a robust procedure on the basis of the Huygens principle (HP) method has previously been developed for haemorrhagic brain stroke detection using MWI techniques [ 12 ]. Head imaging has also been investigated through phantom measurements inside an anechoic chamber, using two antennas in free space and the imaging procedure based on HP [ 12 ]. Since the results coming from measurements inside the anechoic chamber are not representative of a realistic medical device scenario, and there is a medical requirement for a portable brain stroke imaging device, we have come to the decision to apply different signal pre-processing methods to the imaging results collected from a portable MWI device for brain haemorrhage imaging.…”

Section: Introductionmentioning

confidence: 99%

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Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection

Sohani

Puttock

Khalesi

et al. 2020

Sensors

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In this paper, we present an investigation of different artefact removal methods for ultra-wideband Microwave Imaging (MWI) to evaluate and quantify current methods in a real environment through measurements using an MWI device. The MWI device measures the scattered signals in a multi-bistatic fashion and employs an imaging procedure based on Huygens principle. A simple two-layered phantom mimicking human head tissue is realised, applying a cylindrically shaped inclusion to emulate brain haemorrhage. Detection has been successfully achieved using the superimposition of five transmitter triplet positions, after applying different artefact removal methods, with the inclusion positioned at 0°, 90°, 180°, and 270°. The different artifact removal methods have been proposed for comparison to improve the stroke detection process. To provide a valid comparison between these methods, image quantification metrics are presented. An “ideal/reference” image is used to compare the artefact removal methods. Moreover, the quantification of artefact removal procedures through measurements using MWI device is performed.

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Section: Discussionmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection

Sohani

Puttock

Khalesi

et al. 2020

Sensors

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“…As a result, the coupling medium affects the detection of useful scattered “weak” signals. As the antenna array that acquires these signals is confined in a small region surrounding the head, small and compact antennas are commonly used [ 11 , 12 , 13 ]. In addition to small size, MWT antenna arrays for brain imaging must operate in the 0.5–2.0 GHz frequency range to achieve an optimal trade-off between resolution and penetration depth [ 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Metasurface-Enhanced Antennas for Microwave Brain Imaging

Razzicchia

Guo

et al. 2021

Diagnostics

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Stroke is a very frequent disorder and one of the major leading causes of death and disability worldwide. Timely detection of stroke is essential in order to select and perform the correct treatment strategy. Thus, the use of an efficient imaging method for an early diagnosis of this syndrome could result in an increased survival’s rate. Nowadays, microwave imaging (MWI) for brain stroke detection and classification has attracted growing interest due to its non-invasive and non-ionising properties. In this paper, we present a feasibility study with the goal of enhancing MWI for stroke detection using metasurface (MTS) loaded antennas. In particular, three MTS-enhanced antennas integrated in different brain scanners are presented. For the first two antennas, which operate in a coupling medium, we show experimental measurements on an elliptical brain-mimicking gel phantom including cylindrical targets representing the bleeding in haemorrhagic stroke (h-stroke) and the not oxygenated tissue in ischaemic stroke (i-stroke). The reconstructed images and transmission and reflection parameter plots show that the MTS loadings improve the performance of our imaging prototype. Specifically, the signal transmitted across our head model is indeed increased by several dB‘s over the desired frequency range of 0.5–2.0 GHz, and an improvement in the quality of the reconstructed images is shown when the MTS is incorporated in the system. We also present a detailed simulation study on the performance of a new printed square monopole antenna (PSMA) operating in air, enhanced by a MTS superstrate loading. In particular, our previous developed brain scanner operating in an infinite lossy matching medium is compared to two tomographic systems operating in air: an 8-PSMA system and an 8-MTS-enhanced PSMA system. Our results show that our MTS superstrate enhances the antennas’ return loss by around 5 dB and increases the signal difference due to the presence of a blood-mimicking target up to 25 dB, which leads to more accurate reconstructions. In conclusion, MTS structures may be a significant hardware advancement towards the development of functional and ergonomic MWI scanners for stroke detection.

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“…Recent research has also shown the successful detection of lesions which have different dielectric properties to the surrounding medium using UWB Microwave imaging [2]. This holds the potential for detections of cancer and stroke [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

UWB Microwave Imaging for Inclusions Detection: Methodology for Comparing Artefact Removal Algorithms

Puttock

Sohani

Khalesi

et al. 2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Detection of haemorrhagic stroke in simulation and realistic 3-D human head phantom using microwave imaging

Cited by 43 publications

References 23 publications

Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection

Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection

Metasurface-Enhanced Antennas for Microwave Brain Imaging

UWB Microwave Imaging for Inclusions Detection: Methodology for Comparing Artefact Removal Algorithms

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