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  4. Geometry planning and image registration in magnetic particle imaging using bimodal fiducial markers
 
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Geometry planning and image registration in magnetic particle imaging using bimodal fiducial markers

Publikationstyp
Journal Article
Date Issued
2016-06-01
Sprache
English
Author(s)
Werner, Franziska  
Jung, Caroline  
Hofmann, Martin  orcid-logo
Werner, René  
Salamon, Johannes  
Säring, Dennis  
Kaul, Michael  
Them, Kolja  
Weber, Oliver M.  
Mummert, Tobias  
Adam, Gerhard  
Ittrich, Harald  
Knopp, Tobias  
Institut
Biomedizinische Bildgebung E-5  
TORE-URI
http://hdl.handle.net/11420/5665
Journal
Medical physics  
Volume
43
Issue
6
Start Page
2884
End Page
2893
Citation
Medical Physics 6 (43): 2884-2893 (2016-06-01)
Publisher DOI
10.1118/1.4948998
Purpose: Magnetic particle imaging (MPI) is a quantitative imaging modality that allows the distribution of superparamagnetic nanoparticles to be visualized. Compared to other imaging techniques like x-ray radiography, computed tomography (CT), and magnetic resonance imaging (MRI), MPI only provides a signal from the administered tracer, but no additional morphological information, which complicates geometry planning and the interpretation of MP images. The purpose of the authors study was to develop bimodal fiducial markers that can be visualized by MPI and MRI in order to create MP-MR fusion images. Methods: A certain arrangement of three bimodal fiducial markers was developed and used in a combined MRI/MPI phantom and also during in vivo experiments in order to investigate its suitability for geometry planning and image fusion. An algorithm for automated marker extraction in both MR and MP images and rigid registration was established. Results: The developed bimodal fiducial markers can be visualized by MRI and MPI and allow for geometry planning as well as automated registration and fusion of MRMP images. Conclusions: To date, exact positioning of the object to be imaged within the field of view (FOV) and the assignment of reconstructed MPI signals to corresponding morphological regions has been difficult. The developed bimodal fiducial markers and the automated image registration algorithm help to overcome these difficulties.
Subjects
fiducialmarker
geometry planning
MPI
MRI
registration
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