JAS-GAN: Generative Adversarial Network Based Joint Atrium and Scar Segmentations on Unbalanced Atrial Targets
IEEE Journal of Biomedical and Health Informatics(2022)
摘要
Automated and accurate segmentations of left atrium (LA) and atrial scars from late gadolinium-enhanced cardiac magnetic resonance (LGE CMR) images are in high demand for quantifying atrial scars. The previous quantification of atrial scars relies on a two-phase segmentation for LA and atrial scars due to their large volume difference (unbalanced atrial targets). In this paper, we propose an inter...
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关键词
Image segmentation,Task analysis,Adaptive systems,Three-dimensional displays,Visualization,Manuals,Generative adversarial networks
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