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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Bibliographic Details

Published in:	Medical image analysis Vol. 104; p. 103637
Main Authors:	Zhou, Yanjie, Zhou, Feng, Xi, Fengjun, Liu, Yong, Peng, Yun, Carlson, David E., Tu, Liyun
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.08.2025
Subjects:	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 Access:	Get full text
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