Semi-Supervised Volumetric Medical Image Segmentation via Class Prototype Guided Distribution-Aligned Representation Learning

We present SemiCRL, a novel framework for volumetric medical image segmentation that formulates an innovative contrastive learning methodology in a semi-supervised learning setting. We leverage the pseudo-labels generated in semi-supervised learning to guide the selection of negative samples for our...

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Vydané v:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 1931 - 1935
Hlavní autori:	Kong, Xiangyu, Ren, Zeyu, Liu, Lu
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 14.04.2024
Predmet:	Benchmark testing Contrastive Learning Image segmentation Medical Image Segmentation Prototypes Representation learning Self-supervised learning Semi-Supervised Learning Semisupervised learning Signal processing
ISSN:	2379-190X
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