Sayyed Saleh Sayyed Mousavi - IEEE Xplore Author Profile
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Sayyed Saleh Sayyed Mousavi

Publications
4
Citations
9
Publications by Year
20232025
Co-Authors:
Image of author Sayyed Saleh Sayyed Mousavi

Sayyed Saleh Sayyed Mousavi

Affiliation

Communications and Computer Research Center
Ferdowsi University of Mashhad
Mashhad, Iran

Publication Topics

Biography

Sayyed Saleh Sayyed Mousavi was born in Mashhad, Iran, in March 1991. He received the B.S. and M.S. degrees in electrical engineering from the Ferdowsi University of Mashhad, Mashhad, in 2013 and 2016, respectively, where he is currently pursuing the Ph.D. degree.,His current research interests include transformation optic and microwave imaging.(Based on document published on 10 November 2023).
Publications
4
Citations
9
Publications by Year
20232025
Co-Authors:
Author's Published Works

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Reconstruction and Classification of Brain Strokes Using Deep Learning-Based Microwave Imaging

Sayyed Saleh Sayyed Mousavi;Mohammad Saeed Majedi

IEEE Access
Year: 2025 | Volume: 13 | Journal Article |
Prompt identification of the type of brain stroke is a pivotal measure for medical practitioners in commencing therapeutic interventions for patients afflicted with stroke. In this paper, our purpose is to diagnose the type of stroke using high-quality images. This paper presents a novel methodology for image reconstruction using U-Net, followed by the classification of brain stroke type through a...Show More

Reconstruction and Classification of Brain Strokes Using Deep Learning-Based Microwave Imaging

Sayyed Saleh Sayyed Mousavi;Mohammad Saeed Majedi

Year: 2025 | Volume: 13 | Journal Article |

A Modified Microwave Imaging Method for Brain Stroke Detection

Sayyed Saleh Sayyed Mousavi;Mohammad Saeed Majedi

IEEE Transactions on Antennas and Propagation
Year: 2024 | Volume: 72, Issue: 1 | Journal Article |
Cited by: Papers (3)
In this article, a modified microwave imaging method for stroke diagnosis is proposed. This method is based on introducing a suitable initial guess for the distorted Born iterative method (DBIM), which leads to improving the quality of DBIM images. To this end, as a further novelty of the article, we investigate the dependence of the Born iterative method (BIM) and DBIM on the initial guess. We de...Show More

A Modified Microwave Imaging Method for Brain Stroke Detection

Sayyed Saleh Sayyed Mousavi;Mohammad Saeed Majedi

Year: 2024 | Volume: 72, Issue: 1 | Journal Article |

High Quality Brain Image Reconstruction Based on DBIM and U-Net

Sayyed Saleh Sayyed Mousavi;Mohammad Saeed Majedi

2023 30th National and 8th International Iranian Conference on Biomedical Engineering (ICBME)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Diagnosing the type of stroke through brain image reconstruction is a widely employed method that initiates the treatment of stroke patients. Microwave imaging has emerged as a recent technique for image reconstruction, yet it suffers from the drawback of low resolution. In this study, we propose a novel approach to enhancing the quality of reconstructed brain images by leveraging the power of the...Show More

High Quality Brain Image Reconstruction Based on DBIM and U-Net

Sayyed Saleh Sayyed Mousavi;Mohammad Saeed Majedi

Year: 2023 | Conference Paper |

A Quantitative Microwave Imaging Approach for Brain Stroke Classification Based on the Generalized Tikhonov Regularization

Sayyed Saleh Sayyed Mousavi;Mohammad Saeed Majedi

IEEE Access
Year: 2023 | Volume: 11 | Journal Article |
Cited by: Papers (5)
Early diagnosis of stroke type by imaging is one of the most important tasks for stroke patients. In this article, we propose a new approach to reconstruct the brain image with high accuracy and quality. In this approach, first we use the Born iterative method to reconstruct the brain image. Then by comparing this image with a set of MRI-based brain images, using structural similarity index measur...Show More

A Quantitative Microwave Imaging Approach for Brain Stroke Classification Based on the Generalized Tikhonov Regularization

Sayyed Saleh Sayyed Mousavi;Mohammad Saeed Majedi

Year: 2023 | Volume: 11 | Journal Article |

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