Multidimensional perturbed consistency learning for semi‐supervised medical image segmentation

In this article, we propose a novel multidimensional perturbed consistency network (MPCNet) for more accurate semi‐supervised medical image segmentation. Specifically, we develop a multidimensional perturbation by considering the noise itself, the target object and the overall spatial architecture....

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Vydané v:	International journal of imaging systems and technology Ročník 34; číslo 3
Hlavní autori:	Yuan, Enze, Zhao, Bin, Qin, Xiao, Ding, Shuxue
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Hoboken, USA John Wiley & Sons, Inc 01.05.2024 Wiley Subscription Services, Inc
Predmet:	Consistency consistency learning Decoders Image segmentation medical image segmentation Medical imaging multidimensional perturbation Perturbation Semi-supervised learning Supervised learning
ISSN:	0899-9457, 1098-1098
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