Synthetic Full Dose Cardiac PET Images from Low Dose Scans Using Conditional GANs
Author:
Affiliation:
1. Stanford University,Department of Radiology,Stanford,CA,USA,94305
2. University of Turku, Turku University Hospital,Turku PET Center,Turku,Finland,20500
3. University of Turku,Department of Computing,Turku,Finland,20500
Funder
Business Finland
Academy of Finland
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10398888/10398889/10399148.pdf?arnumber=10399148
Reference6 articles.
1. Low-dose PET image noise reduction using deep learning: application to cardiac viability FDG imaging in patients with ischemic heart disease
2. Positron emission tomography myocardial perfusion and glucose metabolism imaging
3. Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods
4. Image-to-Image Translation with Conditional Adversarial Networks
5. Adam: A method for stochastic optimization;Kingma,2014
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