The Dawn of a New Era in Low-Dose PET Imaging

Published Online:
Free first page


  • 1. Cherry SR, Jones T, Karp JS, Qi J, Moses WW, Badawi RD. Total-body PET: maximizing sensitivity to create new opportunities for clinical research and patient care. J Nucl Med 2018;59(1):3–12.
  • 2. Chen KT, Salcedo S, Gong K, et al. An efficient approach to perform MR-assisted PET data optimization in simultaneous PET/MR neuroimaging studies. J Nucl Med 2018 Jun 22 [Epub ahead of print].
  • 3. Chen KT, Gong E, Macruz F. Ultra-low-dose 18 F-florbetaben amyloid PET imaging using deep learning with multi-contrast MRI inputs. Radiology 2019;290:649–656.
  • 4. Kang J, Gao Y, Shi F, Lalush DS, Lin W, Shen D. P online rediction of standard-dose brain PET image by using MRI and low-dose brain [18F]FDG PET images. Med Phys 2015;42(9):5301–5309.
  • 5. Le An, Pei Zhang, Adeli E, et al. Multi-level canonical correlation analysis for standard-dose PET image estimation. IEEE Trans Image Process 2016;25(7):3303–3315.
  • 6. Wang Y, Zhang P, An L, et al. Predicting standard-dose PET image from low-dose PET and multimodal MR images using mapping-based sparse representation. Phys Med Biol 2016;61(2):791–812.
  • 7. Wang Y, Ma G, An L, et al. Semisupervised tripled dictionary learning for standard-dose PET image prediction using low-dose PET and multimodal MRI. IEEE Trans Biomed Eng 2017;64(3):569–579.
  • 8. Xiang L, Qiao Y, Nie D, An L, Wang Q, Shen D. Deep auto-context convolutional neural networks for standard-dose PET image estimation from low-dose PET/MRI. Neurocomputing 2017;267:406–416.
  • 9. Wang Y, Yu B, Wang L, et al. 3D conditional generative adversarial networks for high-quality PET image estimation at low dose. Neuroimage 2018;174:550–562.
  • 10. Xu J, Gong E, Pauly J, Zaharchuk G. 200x Low-dose PET Reconstruction using Deep Learning. Published 2017. Accessed November 8, 2018.

Article History

Received: Nov 8 2018
Revision requested: Nov 12 2018
Revision received: Nov 12 2018
Accepted: Nov 14 2018
Published online: Dec 11 2018
Published in print: Mar 2019