3D microwave tomography of the breast using prior anatomical information
| Autor: | Paul M. Meaney, Keith D. Paulsen, Amir H. Golnabi |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
02 engineering and technology Iterative reconstruction Imaging phantom 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Breast cancer 0202 electrical engineering electronic engineering information engineering medicine Medical imaging Image resolution Multimodal imaging medicine.diagnostic_test business.industry Cancer Soft tissue 020206 networking & telecommunications Magnetic resonance imaging Pattern recognition General Medicine Image segmentation medicine.disease Mr imaging Microwave imaging Artificial intelligence Tomography business Nuclear medicine |
| Zdroj: | Medical Physics. 43:1933-1944 |
| ISSN: | 0094-2405 |
| DOI: | 10.1118/1.4944592 |
| Popis: | Purpose: The authors have developed a new 3D breast image reconstruction technique that utilizes the soft tissue spatial resolution of magnetic resonance imaging(MRI) and integrates the dielectric property differentiation from microwaveimaging to produce a dual modality approach with the goal of augmenting the specificity of MR imaging, possibly without the need for nonspecific contrast agents. The integration is performed through the application of a soft prior regularization which imports segmented geometric meshes generated from MR exams and uses it to constrain the microwave tomography algorithm to recover nearly uniform property distributions within segmented regions with sharp delineation between these internal subzones. Methods: Previous investigations have demonstrated that this approach is effective in 2D simulation and phantom experiments and also in clinical exams. The current study extends the algorithm to 3D and provides a thorough analysis of the sensitivity and robustness to misalignment errors in size and location between the spatial prior information and the actual data. Results: Image results in 3D were not strongly dependent on reconstruction mesh density, and the changes of less than 30% in recovered property values arose from variations of more than 125% in target region size—an outcome which was more robust than in 2D. Similarly, changes of less than 13% occurred in the 3Dimage results from variations in target location of nearly 90% of the inclusion size. Permittivity and conductivity errors were about 5 times and 2 times smaller, respectively, with the 3D spatial prior algorithm in actual phantom experiments than those which occurred without priors. Conclusions: The presented study confirms that the incorporation of structural information in the form of a soft constraint can considerably improve the accuracy of the property estimates in predefined regions of interest. These findings are encouraging and establish a strong foundation for using the soft prior technique in clinical studies, where their microwaveimaging system and MRI can simultaneously collect breast exam data in patients. |
| Databáze: | OpenAIRE |
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