Reduction of bias for sparsity promoting regularization in MPI

Magnetic Particle Imaging (MPI) is a tracer based medical imaging modality with great potential due to its high sensi-tivity, high spatial and temporal resolution, and its ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem, which can be addressed by regularization methods that lead to a reconstruction bias, which is apparent in a systematic mismatch between true and reconstructed tracer distribution. This is expressed in a background signal, a mismatch of the spatial support of the tracer distribution and a mismatch of its values. In this work, MPI reconstruction bias and its impact are investigated and a recently proposed debiasing method with significant bias reduction capabilities is adopted.

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004: Informatik

600: Technik

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https://creativecommons.org/licenses/by/4.0/

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330-Article Text-1746-1-10-20211217.pdf

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Reduction of bias for sparsity promoting regularization in MPI