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Bias-reduction for sparsity promoting regularization in magnetic particle imaging
Citation Link: https://doi.org/10.15480/882.4422
Publikationstyp
Journal Article
Date Issued
2020-09-02
Sprache
English
Author(s)
Institut
TORE-DOI
TORE-URI
Volume
6
Issue
2, Suppl 1
Start Page
1
End Page
3
Article Number
2009041
Citation
International Journal on Magnetic Particle Imaging 6 (2,Suppl 1): 2009041, 1-3 (2020)
Publisher DOI
Scopus ID
Publisher
Infinite Science Publishing
Magnetic Particle Imaging (MPI) is a tracer based medical imaging modality with great potential due to its high sensitivity, high spatial and temporal resolution, and ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem that can be addressed by regularization methods that each lead to a bias. Reconstruction bias in MPI is most apparent in a mismatch between true and reconstructed tracer distribution. This is expressed globally in the spatial support of the distribution and locally in its intensity values. In this work, MPI reconstruction bias and its impact are investigated and a two-step debiasing method with significant bias reduction capabilities is introduced.
DDC Class
004: Informatik
610: Medizin
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281-Article Text-1186-1-10-20200902.pdf
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