Ultra‐low‐dose PET reconstruction using generative adversarial network with feature matching and task‐specific perceptual loss-Reference-Cited by-同舟云学术

Ultra‐low‐dose PET reconstruction using generative adversarial network with feature matching and task‐specific perceptual loss

Published:2019-06-17 Issue:8 Volume:46 Page:3555-3564
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Ouyang Jiahong¹,Chen Kevin T.¹,Gong Enhao²,Pauly John³,Zaharchuk Greg¹²

Affiliation:

1. Department of Radiology Stanford University Stanford CA94305USA

2. Subtle Medical Menlo Park CA94025USA

3. Department of Electrical Engineering Stanford University Stanford CA94305USA

Funder

GE Healthcare

Michael J. Fox Foundation for Parkinson's Research

Foundation of the American Society of Neuroradiology

Center for Outcomes Research and Evaluation, Yale School of Medicine

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.13626

Reference25 articles.

1. The detection rates and tumor clinical/pathological stages of whole-body FDG-PET cancer screening

2. Discrimination between Alzheimer Dementia and Controls by Automated Analysis of Multicenter FDG PET

3. PET/CT in diagnosis of dementia

4. The antibody aducanumab reduces Aβ plaques in Alzheimer’s disease

5. Directorate‐General Environment Nuclear Safety and Civil Protection European Commission.Safety and Civil Protection European Commission. Radiation protection 109: guidance on diagnostic reference levels (DRLs) for medical exposures (radiation protection).1999.

Cited by 130 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MPGAN: Multi Pareto Generative Adversarial Network for the denoising and quantitative analysis of low-dose PET images of human brain;Medical Image Analysis;2024-12

2. Deep learning-based techniques for estimating high-quality full-dose positron emission tomography images from low-dose scans: a systematic review;BMC Medical Imaging;2024-09-11

3. Synthetic Data and its Utility in Pathology and Laboratory Medicine;Laboratory Investigation;2024-08

4. D2GAN: A Dual-Domain Generative Adversarial Network for High-Quality PET Image Reconstruction;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

5. [PET] 8. Recent Progress on AI Image Reconstruction in PET;Japanese Journal of Radiological Technology;2024-06-20