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Titel:

Comparison of Semi- and Un-Supervised Domain Adaptation Methods for Whole-Heart Segmentation

Dokumenttyp:
Proceedings Paper
Autor(en):
Muffoletto, Marica; Xu, Hao; Barbaroux, Hugo; Kunze, Karl P.; Neji, Radhouene; Botnar, Rene; Prieto, Claudia; Rueckert, Daniel; Young, Alistair
Abstract:
Quantification of heart geometry is important in the clinical diagnosis of cardiovascular diseases. Changes in geometry are indicative of remodelling processes as the heart tissue adapts to disease. Coronary Computed Tomography Angiography (CCTA) is considered a first line tool for patients at low or intermediate risk of coronary artery disease, while Coronary Magnetic Resonance Angiography (CMRA) is a promising alternative due to the absence of radiation-induced risks and high performance in th...     »
Zeitschriftentitel:
Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv
Jahr:
2022
Band / Volume:
13593
Seitenangaben Beitrag:
91-100
Volltext / DOI:
doi:10.1007/978-3-031-23443-9_9
Print-ISSN:
0302-9743
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert)
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