Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging
Titel:
Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging
Auteur:
Manini, Chiara Hüllebrand, Markus Walczak, Lars Nordmeyer, Sarah Jarmatz, Lina Kuehne, Titus Stern, Heiko Meierhofer, Christian Harloff, Andreas Erley, Jennifer Kelle, Sebastian Bannas, Peter Trauzeddel, Ralf Felix Schulz-Menger, Jeanette Hennemuth, Anja