nnFormer: Volumetric Medical Image Segmentation via a 3D Transformer

Transformer, the model of choice for natural language processing, has drawn scant attention from the medical imaging community. Given the ability to exploit long-term dependencies, transformers are promising to help atypical convolutional neural networks to learn more contextualized visual represent...

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Veröffentlicht in:	IEEE transactions on image processing Jg. 32; S. 4036 - 4045
Hauptverfasser:	Zhou, Hong-Yu, Guo, Jiansen, Zhang, Yinghao, Han, Xiaoguang, Yu, Lequan, Wang, Liansheng, Yu, Yizhou
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks attention mechanism Boolean functions Data structures Feature extraction Image segmentation Kernel Medical imaging Natural language processing Representations Three dimensional models Three-dimensional displays Transformer Transformers volumetric image segmentation
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
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