3-D Microwave Tomography Using the Soft Prior Regularization Technique: Evaluation in Anatomically Realistic MRI-Derived Numerical Breast Phantoms
| Autor: | Amir H. Golnabi, Paul M. Meaney, Keith D. Paulsen, Shireen D. Geimer |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Permittivity
Materials science Mean squared error 0206 medical engineering Biomedical Engineering Breast Neoplasms 02 engineering and technology Iterative reconstruction Models Biological Multimodal Imaging Article Imaging Three-Dimensional Prior probability medicine Humans Breast Tomography medicine.diagnostic_test Phantoms Imaging Magnetic resonance imaging 020601 biomedical engineering Microwave imaging Regularization (physics) Female Microwave Imaging Microwave Biomedical engineering |
| Zdroj: | IEEE Trans Biomed Eng |
| ISSN: | 1558-2531 0018-9294 |
| DOI: | 10.1109/tbme.2019.2892303 |
| Popis: | Objective: Fusion of magnetic resonance imaging (MRI) breast images with microwave tomography is accomplished through a soft prior technique, which incorporates spatial information (from MRI), i.e., accurate boundary location of different regions of interest, into the regularization process of the microwave image reconstruction algorithm. Methods: Numerical experiments were completed on a set of three-dimensional (3-D) breast geometries derived from MR breast data with different parenchymal densities, as well as a simulated tumor to evaluate the performance over a range of breast shapes, sizes, and property distributions. Results: When the soft prior regularization technique was applied, both permittivity and conductivity relative root mean square error values decreased by more than 87% across all breast densities, except in two cases where the error decrease was only 55% and 78%. In addition, the incorporation of structural priors increased contrast between tumor and fibroglandular tissue by 59% in permittivity and 192% in conductivity. Conclusion: This study confirmed that the soft prior algorithm is robust in 3-D and can function successfully across a range of complex geometries and tissue property distributions. Significance: This study demonstrates that our microwave tomography is capable of recovering accurate tissue property distributions when spatial information from MRI is incorporated through soft prior regularization. |
| Databáze: | OpenAIRE |
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