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Titel:

Faster Diffusion Cardiac MRI with Deep Learning-Based Breath Hold Reduction

Dokumenttyp:
Proceedings Paper
Autor(en):
Tanzer, Michael; Ferreira, Pedro; Scott, Andrew; Khalique, Zohya; Dwornik, Maria; Pennell, Dudley; Yang, Guang; Rueckert, Daniel; Nielles-Vallespin, Sonia
Abstract:
Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) enables us to probe the microstructural arrangement of cardiomyocytes within the myocardium in vivo and non-invasively, which no other imaging modality allows. This innovative technology could revolutionise the ability to perform cardiac clinical diagnosis, risk stratification, prognosis and therapy follow-up. However, DT-CMR is currently inefficient with over six minutes needed to acquire a single 2D static image. Therefore, DT-CMR is current...     »
Zeitschriftentitel:
Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv
Jahr:
2022
Band / Volume:
13413
Seitenangaben Beitrag:
101-115
Volltext / DOI:
doi:10.1007/978-3-031-12053-4_8
Print-ISSN:
0302-9743
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert)
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