Lina Nawwas, M.Sc.

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 212
22529 Hamburg
- Postanschrift -

Technische Universität Hamburg (TUHH)
Institut für Biomedizinische Bildgebung
Gebäude E, Raum 4.044
Am Schwarzenberg-Campus 3
21073 Hamburg

Tel.: 040 / 7410 56309
E-Mail: l.nawwas(at)uke.de
E-Mail: lina.nawwas(at)tuhh.de

Research Interests

  • Magnetic Particle Imaging
  • Image Reconstruction

Curriculum Vitae

Lina Nawwas is a PhD student in the group of Tobias Knopp for experimental Biomedical Imaging at the University Medical Center Hamburg-Eppendorf and the Hamburg University of Technology. In 2016 she earned a Bachelor's degree in Mathematics from An Najah National University in Palestine. From 2016 to 2018 she pursued her Master's degree in Applied Mathematics, majoring Mathematical Modeling for Engineering with MathMods Erasmus Mundus Program in three European universities: University of L’Aquila in Italy, University of Hamburg in Germany, and Gdańsk University of Technology in Poland.

Journal Publications

[168323]
Title: Reduction of bias for sparsity promoting regularization in MPI.
Written by: L. Nawwas, C. Brandt, P. Szwargulski, T. Knopp, and M. Möddel
in: <em>International Journal on Magnetic Particle Imaging</em>. (2021).
Volume: <strong>7</strong>. Number: (2),
on pages: 1-13
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DOI: https://doi.org/10.18416/IJMPI.2021.2112002
URL: https://journal.iwmpi.org/index.php/iwmpi/article/view/330
ARXIVID:
PMID:

[www] [BibTex]

Note: article, artifact

Abstract: 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 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.

Conference Proceedings

[168323]
Title: Reduction of bias for sparsity promoting regularization in MPI.
Written by: L. Nawwas, C. Brandt, P. Szwargulski, T. Knopp, and M. Möddel
in: <em>International Journal on Magnetic Particle Imaging</em>. (2021).
Volume: <strong>7</strong>. Number: (2),
on pages: 1-13
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: https://doi.org/10.18416/IJMPI.2021.2112002
URL: https://journal.iwmpi.org/index.php/iwmpi/article/view/330
ARXIVID:
PMID:

[www] [BibTex]

Note: article, artifact

Abstract: 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 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.