ViT-UperNet: a hybrid vision transformer with unified-perceptual-parsing network for medical image segmentation

Abstract The existing image semantic segmentation models have low accuracy in detecting tiny targets or multi-targets at overlapping regions. This work proposes a hybrid vision transformer with unified-perceptual-parsing network (ViT-UperNet) for medical image segmentation. A self-attention mechanis...

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Autors principals:	Yang Ruiping, Liu Kun, Xu Shaohua, Yin Jian, Zhang Zhen
Format:	Artigo
Idioma:	Inglês
Publicat:	Springer 2024-02-01
Col·lecció:	Complex & Intelligent Systems
Matèries:	Medical image segmentation Deep learning Self-attention mechanism Masked autoencoder
Accés en línia:	https://doi.org/10.1007/s40747-024-01359-6
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