Review of microwave imaging algorithms for stroke detection
Jinzhen Liu1,2, Liming Chen1,2, Hui Xiong3,4
1The School of Control Science and Engineering, Tiangong University, Tianjin, 300387, People's Republic of China.
Medical & Biological Engineering & Computing
|May 24, 2023
Summary
This paper reviews microwave imaging algorithms for stroke detection, highlighting their advantages over traditional methods. It explores advancements in microwave tomography, radar, and deep learning for improved stroke imaging and diagnosis.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Electromagnetics
Background:
- Microwave imaging is an emerging medical imaging technique.
- Traditional stroke detection methods pose risks like ionizing radiation.
- Microwave imaging offers a cost-effective and safe alternative for stroke diagnosis.
Purpose of the Study:
- To review and analyze the development of microwave imaging algorithms for stroke image reconstruction.
- To provide a systematic overview of current research, challenges, and future trends in this field.
Main Methods:
- Review of common microwave imaging algorithms, including microwave tomography, radar imaging, and deep learning.
- Analysis of signal collection using microwave antennas and image reconstruction techniques.
- Presentation of algorithm classification diagrams and flowcharts.
Main Results:
- Identified key research hotspots in microwave imaging for stroke, focusing on algorithm design and improvement.
- Systematically expounded on the concepts, current status, and difficulties of these algorithms.
- Highlighted the potential for enhanced stroke detection and diagnosis.
Conclusions:
- Microwave imaging algorithms are crucial for advancing stroke detection.
- Further research is needed to overcome current challenges and explore future development trends.
- This review provides a comprehensive resource for understanding microwave imaging in stroke diagnosis.
