Review of microwave imaging algorithms for stroke detection

Liu, Jinzhen; Chen, Liming; Xiong, Hui; Han, Yanbo

doi:10.1007/s11517-023-02848-5

Cited by 7 publications

(5 citation statements)

References 97 publications

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“…To verify the above theory, the far-field patterns of FBSLWA with L = 20λ 0 and k s = 1.3k 0 (where λ 0 is the free space wavelength and k 0 is the wavenumber in free space at 11.0 GHz) are calculated using equations (1)- (5). For different main beam directions, the grating lobe pointing angles with different element spacing d are shown in figure 2.…”

Section: Influence Of Elements Spacing On the Steering Range Without ...mentioning

confidence: 94%

“…The beam steering antennas are widely used in low earth orbit satellite communication systems, fifth-generation (5G) mobile wireless communication systems, the forthcoming * Authors to whom any correspondence should be addressed. sixth-generation (6G) mobile wireless communication systems, medical microwave imaging, and so on [1][2][3][4][5]. Moreover, the beam steering antennas should have the advantages of low profile, low cost, and wide-angle scanning [6].…”

Section: Introductionmentioning

confidence: 99%

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A 1-bit phase reconfigurable fixed-frequency wide-angle steering leaky-wave antenna

Han,

Meng,

Wang

et al. 2023

J. Phys. D: Appl. Phys.

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A 1-bit phase reconfigurable fixed-frequency beam steering leaky-wave antenna (FBSLWA) with wide-angle steering is proposed in this paper. By controlling two p-i-n diodes on the branches of the element, a stable 180° phase difference is realized. Moreover, the open stop-band effect at the broadside radiation is suppressed by reducing the reflection coefficients of the element. The proposed FBSLWA can achieve wide-angle steering within a frequency bandwidth of 10.4 GHz to 11.8 GHz. As for the measured results, they show that the achievable beam steering ranges of the FBSLWA at 10.4 GHz, 11.0 GHz, and 11.8 GHz are -61° to +59°, -64° to +71°, and -62° to +58° respectively, with measured peak gains of 12.1 dBi, 13.9 dBi, and 11.7 dBi.

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Section: Influence Of Elements Spacing On the Steering Range Without ...mentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

A 1-bit phase reconfigurable fixed-frequency wide-angle steering leaky-wave antenna

Han,

Meng,

Wang

et al. 2023

J. Phys. D: Appl. Phys.

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“…The relationship for the whole process can be expressed as (5), where Ψ represents the non-linear operation of MUNET:…”

Section: Ed-munet Approachmentioning

confidence: 99%

“…Microwave imaging was first used to study stroke by Semenov et al 4 The traditional microwave imaging techniques for stroke detection include radar imaging and microwave tomography. 5 Although radar imaging can reconstruct images relatively quickly, it cannot classify stroke types, and the resolution of reconstructed images needs to be improved. 6 The commonly used methods for microwave tomography include the Newton method 7 and the Born iterative method.…”

Section: Introductionmentioning

confidence: 99%

“…Various reconstruction algorithms have been proposed to obtain accurate stroke images. Microwave imaging was first used to study stroke by Semenov et al 4 The traditional microwave imaging techniques for stroke detection include radar imaging and microwave tomography 5 . Although radar imaging can reconstruct images relatively quickly, it cannot classify stroke types, and the resolution of reconstructed images needs to be improved 6 .…”

Section: Introductionmentioning

confidence: 99%

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An encoder–decoder and modified U‐Net network for microwave imaging of stroke

Liu,

Chen,

Xiong

2023

Int J Imaging Syst Tech

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Microwave imaging has been widely used in stroke diagnosis as a non‐invasive, ionizing radiation‐free imaging method. However, the electromagnetic inverse scattering problems of microwave imaging are nonlinear and ill‐posed. To further improve the accuracy of microwave imaging algorithms to identify and reconstruct stroke regions. A novel Encoder‐Decoder and Modified U‐Net (ED‐MUNET) network for microwave imaging of stroke is proposed. The newly proposed ED‐MUNET method accomplishes the initial imaging from scattered data to stroke images through an encoder–decoder in the first step. In the second step, the feature information of the reconstructed image is extracted through the modified U‐Net network, and the reconstruction from the rough stroke image to the high‐resolution image is realized. The second step avoids black‐box operations and improves image accuracy. ED‐MUNET has fewer artifacts, the relative reconstruction error is less than 0.05, and the reconstructed images are clearer, according to the comparative experiments with other networks. The experimental results showed the superiority of the proposed method for reconstructing stroke images.

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A multi-scale attention residual-based U-Net network for stroke electrical impedance tomography

Liu,

Chen,

Xiong

et al. 2024

Review of Scientific Instruments

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Electrical impedance tomography (EIT), a non-invasive, radiation-free, and convenient imaging technique, has been widely used in the diagnosis of stroke. However, due to soft-field nonlinearity and the ill-posed inverse problem, EIT images always suffer from low spatial resolution. Therefore, a multi-scale convolutional attention residual-based U-Net (MARU-Net) network is proposed for stroke reconstruction. Based on the U-Net network, a residual module and a multi-scale convolutional attention module are added to the concatenation layer. The multi-scale module extracts feature information of different sizes, the attention module strengthens the useful information, and the residual module improves the performance of the network. Based on the above advantages, the network is used in the EIT system for stroke imaging. Compared with convolutional neural networks and one-dimensional convolutional neural networks, the MARU-Net network has fewer artifacts, and the reconstructed image is clear. At the same time, the reduction of noisy artifacts in the MARU-Net network is verified. The results show that the image correlation coefficient of the reconstructed image with noise is greater than 0.87. Finally, the practicability of the network is verified by a model physics experiment.

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Review of microwave imaging algorithms for stroke detection

Cited by 7 publications

References 97 publications

A 1-bit phase reconfigurable fixed-frequency wide-angle steering leaky-wave antenna

A 1-bit phase reconfigurable fixed-frequency wide-angle steering leaky-wave antenna

An encoder–decoder and modified U‐Net network for microwave imaging of stroke

A multi-scale attention residual-based U-Net network for stroke electrical impedance tomography

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