Synthetic Microwave Focusing Techniques for Medical Imaging: Fundamentals, Limitations, and Challenges
Synthetic microwave focusing methods have been widely adopted in qualitative medical imaging to detect and localize anomalies based on their electromagnetic scattering signatures. This paper discusses the principles, challenges, and limitations of synthetic microwave-focusing techniques in medical a...
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| Format: | Article |
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MDPI AG
2024-10-01
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| Series: | Biosensors |
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| Online Access: | https://www.mdpi.com/2079-6374/14/10/498 |
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| author | Younis M. Abbosh Kamel Sultan Lei Guo Amin Abbosh |
| author_facet | Younis M. Abbosh Kamel Sultan Lei Guo Amin Abbosh |
| author_sort | Younis M. Abbosh |
| collection | DOAJ |
| description | Synthetic microwave focusing methods have been widely adopted in qualitative medical imaging to detect and localize anomalies based on their electromagnetic scattering signatures. This paper discusses the principles, challenges, and limitations of synthetic microwave-focusing techniques in medical applications. It is shown that the various focusing techniques, including time reversal, confocal imaging, and delay-and-sum, are all based on the scalar solution of the electromagnetic scattering problem, assuming the imaged object, i.e., the tissue or object, is linear, reciprocal, and time-invariant. They all aim to generate a qualitative image, revealing any strong scatterer within the imaged domain. The differences among these techniques lie only in the assumptions made to derive the solution and create an image of the relevant tissue or object. To get a fast solution using limited computational resources, those methods assume the tissue is homogeneous and non-dispersive, and thus, a simplified far-field Green’s function is used. Some focusing methods compensate for dispersive effects and attenuation in lossy tissues. Other approaches replace the simplified Green’s function with more representative functions. While these focusing techniques offer benefits like speed and low computational requirements, they face significant ongoing challenges in real-life applications due to their oversimplified linear solutions to the complex problem of non-linear medical microwave imaging. This paper discusses these challenges and potential solutions. |
| format | Article |
| id | doaj-art-0bf88363fc2d41f2ad885a881655e52a |
| institution | OA Journals |
| issn | 2079-6374 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biosensors |
| spelling | doaj-art-0bf88363fc2d41f2ad885a881655e52a2025-08-20T02:11:09ZengMDPI AGBiosensors2079-63742024-10-01141049810.3390/bios14100498Synthetic Microwave Focusing Techniques for Medical Imaging: Fundamentals, Limitations, and ChallengesYounis M. Abbosh0Kamel Sultan1Lei Guo2Amin Abbosh3College of Electronics Engineering, Ninevah University, Mosul 41002, IraqSchool of EECS, The University of Queensland, St Lucia, QLD 4072, AustraliaSchool of EECS, The University of Queensland, St Lucia, QLD 4072, AustraliaSchool of EECS, The University of Queensland, St Lucia, QLD 4072, AustraliaSynthetic microwave focusing methods have been widely adopted in qualitative medical imaging to detect and localize anomalies based on their electromagnetic scattering signatures. This paper discusses the principles, challenges, and limitations of synthetic microwave-focusing techniques in medical applications. It is shown that the various focusing techniques, including time reversal, confocal imaging, and delay-and-sum, are all based on the scalar solution of the electromagnetic scattering problem, assuming the imaged object, i.e., the tissue or object, is linear, reciprocal, and time-invariant. They all aim to generate a qualitative image, revealing any strong scatterer within the imaged domain. The differences among these techniques lie only in the assumptions made to derive the solution and create an image of the relevant tissue or object. To get a fast solution using limited computational resources, those methods assume the tissue is homogeneous and non-dispersive, and thus, a simplified far-field Green’s function is used. Some focusing methods compensate for dispersive effects and attenuation in lossy tissues. Other approaches replace the simplified Green’s function with more representative functions. While these focusing techniques offer benefits like speed and low computational requirements, they face significant ongoing challenges in real-life applications due to their oversimplified linear solutions to the complex problem of non-linear medical microwave imaging. This paper discusses these challenges and potential solutions.https://www.mdpi.com/2079-6374/14/10/498synthetic focusingelectromagnetic imagingmicrowave imagingmedical imagingdelay and sumconfocal imaging |
| spellingShingle | Younis M. Abbosh Kamel Sultan Lei Guo Amin Abbosh Synthetic Microwave Focusing Techniques for Medical Imaging: Fundamentals, Limitations, and Challenges Biosensors synthetic focusing electromagnetic imaging microwave imaging medical imaging delay and sum confocal imaging |
| title | Synthetic Microwave Focusing Techniques for Medical Imaging: Fundamentals, Limitations, and Challenges |
| title_full | Synthetic Microwave Focusing Techniques for Medical Imaging: Fundamentals, Limitations, and Challenges |
| title_fullStr | Synthetic Microwave Focusing Techniques for Medical Imaging: Fundamentals, Limitations, and Challenges |
| title_full_unstemmed | Synthetic Microwave Focusing Techniques for Medical Imaging: Fundamentals, Limitations, and Challenges |
| title_short | Synthetic Microwave Focusing Techniques for Medical Imaging: Fundamentals, Limitations, and Challenges |
| title_sort | synthetic microwave focusing techniques for medical imaging fundamentals limitations and challenges |
| topic | synthetic focusing electromagnetic imaging microwave imaging medical imaging delay and sum confocal imaging |
| url | https://www.mdpi.com/2079-6374/14/10/498 |
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