AS-Net: Fast Photoacoustic Reconstruction With Multi-Feature Fusion From Sparse Data

Guo, Mengjie1; Lan, Hengrong1,2,3; Yang, Changchun1; Liu, Jiang4,5; Gao, Fei1,6

2022

10.1109/TCI.2022.3155379

IEEE Transactions on Computational Imaging   影响因子和分区

2573-0436

Attention deep learning photoacoustic tomography reconstruction sparse sampling

SCI ; EI

通讯

WOS:000769970400001

20221011757788

Compressed sensing ; Deep learning ; Medical imaging ; Photoacoustic effect ; Semantics

Biomedical Engineering:461.1 ; Ergonomics and Human Factors Engineering:461.4 ; Information Theory and Signal Processing:716.1 ; Light/Optics:741.1 ; Imaging Techniques:746 ; Acoustic Waves:751.1

IEEE

1.ShanghaiTech Univ, Sch Informat Sci & Technol, Hybrid Imaging Syst Lab, Shanghai 201210, Peoples R China
2.Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Shanghai 200050, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen 518055, Guangdong, Peoples R China
5.Chinese Acad Sci, Cixi Inst Biomed Engn, Shanghai 200050, Peoples R China
6.Shanghai Engn Res Ctr Energy Efficient & Custom A, Shanghai 201210, Peoples R China

Guo, Mengjie,Lan, Hengrong,Yang, Changchun,et al. AS-Net: Fast Photoacoustic Reconstruction With Multi-Feature Fusion From Sparse Data[J]. IEEE Transactions on Computational Imaging,2022,8:215-223.

Guo, Mengjie,Lan, Hengrong,Yang, Changchun,Liu, Jiang,&Gao, Fei.(2022).AS-Net: Fast Photoacoustic Reconstruction With Multi-Feature Fusion From Sparse Data.IEEE Transactions on Computational Imaging,8,215-223.

Guo, Mengjie,et al."AS-Net: Fast Photoacoustic Reconstruction With Multi-Feature Fusion From Sparse Data".IEEE Transactions on Computational Imaging 8(2022):215-223.