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Feasibility of a Generative Adversarial Network for Artifact Removal in Experimental Photoacoustic Imaging

  • Published:2022-08 Issue:8 Volume:48 Page:1628-1643
  • ISSN:0301-5629
  • Container-title:Ultrasound in Medicine & Biology
  • language:en
  • Short-container-title:Ultrasound in Medicine & Biology

Author:

Shahid Husnain,Khalid Adnan,Yue Yaoting,Liu Xin,Ta Dean

Funder

Program of Shanghai Academic Research Leader

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Acoustics and Ultrasonics,Radiology, Nuclear Medicine and imaging,Biophysics,Radiological and Ultrasound Technology

Reference48 articles.

1. Deep learning for photoacoustic tomography from sparse data;Antholzer;Inverse Prob Sci Eng,2019

2. Wasserstein generative adversarial networks;Arjovsky;Int Conf Mach Learn,2017

3. Accelerated high-resolution photoacoustic tomography via compressed sensing;Arridge;Phys Med Biol,2016

4. Biomedical photoacoustic imaging;Beard;Interface Focus,2011

5. Deep learning optoacoustic tomography with sparse data;Davoudi;Nat Machine Intell,2019

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