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Titel:

Mesh-Based 3D Motion Tracking in Cardiac MRI Using Deep Learning

Dokumenttyp:
Proceedings Paper
Autor(en):
Meng, Qingjie; Bai, Wenjia; Liu, Tianrui; O'Regan, Declan P.; Rueckert, Daniel
Abstract:
3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and diagnosis of cardiovascular diseases. Most of the previous methods focus on estimating pixel-/voxel-wise motion fields in the full image space, which ignore the fact that motion estimation is mainly relevant and useful within the object of interest, e.g., the heart. In this work, we model the heart as a 3D geometric mesh and propose a novel deep learning-based method tha...     »
Zeitschriftentitel:
Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv
Jahr:
2022
Band / Volume:
13436
Seitenangaben Beitrag:
248-258
Volltext / DOI:
doi:10.1007/978-3-031-16446-0_24
Print-ISSN:
0302-9743
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert)
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