Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Jürgen Frikel"'
Publikováno v:
Mathematics, Vol 12, Iss 10, p 1606 (2024)
In a number of tomographic applications, data cannot be fully acquired, resulting in severely underdetermined image reconstruction. Conventional methods in such cases lead to reconstructions with significant artifacts. To overcome these artifacts, re
Externí odkaz:
https://doaj.org/article/c139c678b09d4eba9bf7c415cbd8a46b
Publikováno v:
Mathematics, Vol 10, Iss 8, p 1318 (2022)
In this paper, we consider the problem of feature reconstruction from incomplete X-ray CT data. Such incomplete data problems occur when the number of measured X-rays is restricted either due to limit radiation exposure or due to practical constraint
Externí odkaz:
https://doaj.org/article/b60a27fe8f1c4130af67f2b222c8aa7a
Solving inverse problems is central to a variety of important applications, such as biomedical image reconstruction and non-destructive testing. These problems are characterized by the sensitivity of direct solution methods with respect to data pertu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::74985468ed77a816778d5abfbedb6dc7
http://arxiv.org/abs/2208.08500
http://arxiv.org/abs/2208.08500
Publikováno v:
Bildverarbeitung für die Medizin 2021 ISBN: 9783658331979
Bildverarbeitung für die Medizin
Bildverarbeitung für die Medizin
We present two methods that combine image reconstruction and edge detection in computed tomography (CT) scans. Our first method is as an extension of the prominent filtered backprojection algorithm. In our second method we employ \(\mathcal{l}^{1}\)-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::940667cfba176eb677d61d81e0f9278d
https://doi.org/10.1007/978-3-658-33198-6_37
https://doi.org/10.1007/978-3-658-33198-6_37
The characteristic feature of inverse problems is their instability with respect to data perturbations. In order to stabilize the inversion process, regularization methods have to be developed and applied. In this work we introduce and analyze the co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99a4efdb6c3f59ac8acd44e06341af76
http://arxiv.org/abs/2008.06219
http://arxiv.org/abs/2008.06219
We derive a new 3D model for magnetic particle imaging (MPI) that is able to incorporate realistic magnetic fields in the reconstruction process. In real MPI scanners, the generated magnetic fields have distortions that lead to deformed magnetic low-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb9e678ea775a05b2fbffa3fdc84fff5
http://hdl.handle.net/11577/3362578
http://hdl.handle.net/11577/3362578
Autor:
Jürgen Frikel, Markus Haltmeier
Publikováno v:
Trends in Mathematics ISBN: 9783030471736
We analyze sparse frame based regularization of inverse problems by means of a diagonal frame decomposition (DFD) for the forward operator, which generalizes the SVD. The DFD allows to define a non-iterative (direct) operator-adapted frame thresholdi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0412c112d69b88e5a897f06a7c074df0
https://doi.org/10.1007/978-3-030-47174-3_10
https://doi.org/10.1007/978-3-030-47174-3_10
Autor:
Andreas Weinmann, Alexander E. Weber, Mandy Ahlborg, Martin Möddel, Gael Bringout, Christina Brandt, Christian Kaethner, Tobias Knopp, Martin Storath, Thorsten M. Buzug, Thomas März, Wolfgang Erb, Jürgen Frikel
Publikováno v:
Inverse Probl. 34:055012 (2018)
Magnetic particle imaging (MPI) is a promising new in-vivo medical imaging modality in which distributions of super-paramagnetic nanoparticles are tracked based on their response in an applied magnetic field. In this paper we provide a mathematical a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e39397fe68a6c43fb9152c1643f1fc4d
http://hdl.handle.net/11577/3368971
http://hdl.handle.net/11577/3368971
Autor:
Tobias Lasser, Peter B. Noël, Elena Eggl, Matthias Wieczorek, Laurent Demaret, Felix K. Kopp, Jakob Vogel, Jürgen Frikel, Franz Pfeiffer
Publikováno v:
Medical Physics. 42:1555-1565
Purpose: Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36a3fcfd56b53c99ca3061f3ab718db7
https://doi.org/10.1118/1.4914368
https://doi.org/10.1118/1.4914368
Autor:
Jürgen Frikel, Eric Todd Quinto
Publikováno v:
SIAM Journal on Applied Mathematics. 75:703-725
We develop a paradigm using microlocal analysis that allows one to characterize the visible and added singularities in a broad range of incomplete data tomography problems. We give precise characterizations for photoacoustic and thermoacoustic tomogr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc25bf923bd3f37a57d6583b4b522217
https://doi.org/10.1137/140977709
https://doi.org/10.1137/140977709