Abstract
This paper proposes a transformer-based neural network, for segmenting the images of human tissues obtained by inverse scattering method. Firstly, the distribution image of relative permittivity for the human tissue is obtained by the subspace-based optimization method (SOM). Then the obtained results are fed into a transformer-based network to output a segmentation mask. Numerical results verify that this method can get clear edges for different tissues, and it can achieve accurate classification for human tissue imaging.
Original language | English |
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Title of host publication | 2024 IEEE International Symposium on Antennas and Propagation and INC/USNCURSI Radio Science Meeting, AP-S/INC-USNC-URSI 2024 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 251-252 |
Number of pages | 2 |
ISBN (Electronic) | 9798350369908 |
DOIs | |
Publication status | Published - 2024 |
Event | 2024 IEEE International Symposium on Antennas and Propagation and INC/USNCURSI Radio Science Meeting, AP-S/INC-USNC-URSI 2024 - Florence, Italy Duration: 14 Jul 2024 → 19 Jul 2024 |
Publication series
Name | IEEE Antennas and Propagation Society, AP-S International Symposium (Digest) |
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ISSN (Print) | 1522-3965 |
Conference
Conference | 2024 IEEE International Symposium on Antennas and Propagation and INC/USNCURSI Radio Science Meeting, AP-S/INC-USNC-URSI 2024 |
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Country/Territory | Italy |
City | Florence |
Period | 14/07/24 → 19/07/24 |
Keywords
- imaging segmentation
- inverse scattering method
- SOM
- transformer-based network
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Du, N., & Ye, X. (2024). A Machine Learning-based Inverse Scattering Method for Biomedical Imaging Segmentation. In 2024 IEEE International Symposium on Antennas and Propagation and INC/USNCURSI Radio Science Meeting, AP-S/INC-USNC-URSI 2024 - Proceedings (pp. 251-252). (IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AP-S/INC-USNC-URSI52054.2024.10686379