Automatic upper airway segmentation in static and dynamic MRI via anatomy‐guided convolutional neural networks

Purpose Upper airway segmentation on MR images is a prerequisite step for quantitatively studying the anatomical structure and function of the upper airway and surrounding tissues. However, the complex variability of intensity and shape of anatomical structures and different modes of image acquisiti...

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Veröffentlicht in:	Medical physics (Lancaster) Jg. 49; H. 1; S. 324 - 342
Hauptverfasser:	Xie, Lipeng, Udupa, Jayaram K., Tong, Yubing, Torigian, Drew A., Huang, Zihan, Kogan, Rachel M., Wootton, David, Choy, Kok R., Sin, Sanghun, Wagshul, Mark E., Arens, Raanan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.01.2022
Schlagworte:	convolutional neural networks dynamic MRI Humans Image Processing, Computer-Assisted image segmentation Lung Magnetic Resonance Imaging Neural Networks, Computer static MRI upper airway upper airway convolutional neural networks image segmentation static MRI dynamic MRI
ISSN:	0094-2405, 2473-4209, 2473-4209
Online-Zugang:	Volltext
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