Efficient few-shot medical image segmentation via self-supervised variational autoencoder

Few-shot medical image segmentation typically uses a joint model for registration and segmentation. The registration model aligns a labeled atlas with unlabeled images to form initial masks, which are then refined by the segmentation model. However, inevitable spatial misalignments during registrati...

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Veröffentlicht in:	Medical image analysis Jg. 104; S. 103637
Hauptverfasser:	Zhou, Yanjie, Zhou, Feng, Xi, Fengjun, Liu, Yong, Peng, Yun, Carlson, David E., Tu, Liyun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.08.2025
Schlagworte:	Algorithms Autoencoder Few-shot learning Humans Image Interpretation, Computer-Assisted - methods Image Processing, Computer-Assisted - methods Image reconstruction Magnetic Resonance Imaging Medical image segmentation Supervised Machine Learning Variational autoencoder Variational autoencoder Few-shot learning Image reconstruction Medical image segmentation
ISSN:	1361-8415, 1361-8423, 1361-8423
Online-Zugang:	Volltext
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