Dictionary-based background signal estimation for magnetic particle imaging
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Dictionary-based background signal estimation for magnetic particle imaging. / Knopp, Tobias; Grosser, Mirco; Graeser, Matthias; Gerkmann, Timo; Moddel, Martin.
2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021. IEEE Computer Society, 2021. S. 1540-1543 9434048 (Proceedings - International Symposium on Biomedical Imaging; Band 2021-April).Publikationen: SCORING: Beitrag in Buch/Sammelwerk › Konferenzbeitrag - Aufsatz in Konferenzband › Forschung › Begutachtung
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TY - CHAP
T1 - Dictionary-based background signal estimation for magnetic particle imaging
AU - Knopp, Tobias
AU - Grosser, Mirco
AU - Graeser, Matthias
AU - Gerkmann, Timo
AU - Moddel, Martin
N1 - Publisher Copyright: © 2021 IEEE.
PY - 2021/4/13
Y1 - 2021/4/13
N2 - Magnetic Particle Imaging is a highly sensitive tracer-based imaging method able to image as little as a nanogram of tracer material. In practice, background signals stemming from imperfections in the scanner instrumentation make it challenging to achieve these very high sensitivities. In case where the background signal is static over time it can be simply subtracted using an empty reference measurement. In this work we develop a method that is capable of handling dynamic background signals. Since the particle signal and the background signal are superimposed, we propose to perform a joint estimation of both quantities. The background signal space is modeled by a dictionary of background signals, build from a set of representative drifting background measurements. The proposed method is evaluated on experimentally and it is shown that it is capable of accurately estimating the background and tracer signal in a dynamic phantom experiment.
AB - Magnetic Particle Imaging is a highly sensitive tracer-based imaging method able to image as little as a nanogram of tracer material. In practice, background signals stemming from imperfections in the scanner instrumentation make it challenging to achieve these very high sensitivities. In case where the background signal is static over time it can be simply subtracted using an empty reference measurement. In this work we develop a method that is capable of handling dynamic background signals. Since the particle signal and the background signal are superimposed, we propose to perform a joint estimation of both quantities. The background signal space is modeled by a dictionary of background signals, build from a set of representative drifting background measurements. The proposed method is evaluated on experimentally and it is shown that it is capable of accurately estimating the background and tracer signal in a dynamic phantom experiment.
KW - Background Signals
KW - Dictionary Approach
KW - Image Reconstruction
KW - Magnetic Particle Imaging
UR - http://www.scopus.com/inward/record.url?scp=85107173642&partnerID=8YFLogxK
U2 - 10.1109/ISBI48211.2021.9434048
DO - 10.1109/ISBI48211.2021.9434048
M3 - Conference contribution - Article for conference
AN - SCOPUS:85107173642
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 1540
EP - 1543
BT - 2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021
PB - IEEE Computer Society
T2 - 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021
Y2 - 13 April 2021 through 16 April 2021
ER -