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Sinogram denoising via attention residual dense convolutional neural network for low-dose computed tomography

NUCLEAR ELECTRONICS AND INSTRUMENTATION | Updated：2021-05-10

- Sinogram denoising via attention residual dense convolutional neural network for low-dose computed tomography Cover Article Enhanced Publication
- Nuclear Science and Techniques Vol.32, Issue 4, (2021)
- Affiliations：
  
  Key Laboratory of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University,Chongqing,China,400044;School of Data Science, Tongren University,Tongren,China,554300;School of Microelectronics and Communication Engineering, Chongqing University,Chongqing,China,400044;Department of Biomedical Engineering, Rensselaer Polytechnic Institute,Troy,New York,USA,12180
- Author bio：
- Funds：
- DOI：10.1007/s41365-021-00874-2 CLC：
- Published：01 April 2021，
  
  Published Online：19 April 2021，
  
  Received：04 December 2020，
  
  Revised：21 January 2021，
  
  Accepted：22 January 2021
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Cite this article
Yin-Jin Ma, Yong Ren, Peng Feng, et al. Sinogram denoising via attention residual dense convolutional neural network for low-dose computed tomography. [J]. Nuclear Science and Techniques 32(4):41(2021)
DOI：

Yin-Jin Ma, Yong Ren, Peng Feng, et al. Sinogram denoising via attention residual dense convolutional neural network for low-dose computed tomography. [J]. Nuclear Science and Techniques 32(4):41(2021) DOI： 10.1007/s41365-021-00874-2.

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Sinogram denoising via attention residual dense convolutional neural network for low-dose computed tomography Cover Article Enhanced Publication