DS-TransUNet: Dual Swin Transformer U-Net for Medical Image Segmentation

Automatic medical image segmentation has made great progress owing to powerful deep representation learning. Inspired by the success of self-attention mechanism in transformer, considerable efforts are devoted to designing the robust variants of the encoder-decoder architecture with transformer. How...

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Vydané v:	IEEE transactions on instrumentation and measurement Ročník 71; s. 1 - 15
Hlavní autori:	Lin, Ailiang, Chen, Bingzhi, Xu, Jiayu, Zhang, Zheng, Lu, Guangming, Zhang, David
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Coders Computer architecture Data integration Decoding Feature extraction Hierarchical swin transformer Image enhancement Image quality Image segmentation long-range contextual information Medical diagnostic imaging medical image segmentation Medical imaging Representations Semantic segmentation Semantics Task analysis transformer interactive fusion~(TIF) module Transformers
ISSN:	0018-9456, 1557-9662
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