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Titel:

Attention-Aware Non-Rigid Image Registration for Accelerated MR Imaging.

Dokumenttyp:
Journal Article
Autor(en):
Ghoul, Aya; Pan, Jiazhen; Lingg, Andreas; Kubler, Jens; Krumm, Patrick; Hammernik, Kerstin; Rueckert, Daniel; Gatidis, Sergios; Kustner, Thomas
Abstract:
Accurate motion estimation at high acceleration factors enables rapid motion-compensated reconstruction in Magnetic Resonance Imaging (MRI) without compromising the diagnostic image quality. In this work, we introduce an attention-aware deep learning-based framework that can perform non-rigid pairwise registration for fully sampled and accelerated MRI. We extract local visual representations to build similarity maps between the registered image pairs at multiple resolution levels and additionall...     »
Zeitschriftentitel:
IEEE Trans Med Imaging
Jahr:
2024
Band / Volume:
43
Heft / Issue:
8
Seitenangaben Beitrag:
3013-3026
Volltext / DOI:
doi:10.1109/TMI.2024.3385024
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/39088484
Print-ISSN:
0278-0062
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert)
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