| Residential College | false |
| Status | 已發表Published |
| Generative Adversarial Network for Denoising in Dual Gated Myocardial Perfusion SPECT Using a Population of Phantoms and Clinical Data | |
Sun JZ1 ; Zhang Q1; Zhang D1 ; Pretorius PH2; King MA2; Mo SP(莫昇萍)1
| |
| 2019-10 | |
| Conference Name | 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference |
| Conference Date | 26/10/2019-02/11/2019 |
| Conference Place | Manchester |
| Country | UK |
| Document Type | Conference paper |
| Collection | DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING |
| Corresponding Author | Sun JZ; Zhang Q |
| Affiliation | 1.University of Macau 2.UMASS Medical School |
| First Author Affilication | University of Macau |
| Corresponding Author Affilication | University of Macau |
| Recommended Citation GB/T 7714 | Sun JZ,Zhang Q,Zhang D,et al. Generative Adversarial Network for Denoising in Dual Gated Myocardial Perfusion SPECT Using a Population of Phantoms and Clinical Data[C], 2019. |
| APA | Sun JZ., Zhang Q., Zhang D., Pretorius PH., King MA., & Mo SP (2019). Generative Adversarial Network for Denoising in Dual Gated Myocardial Perfusion SPECT Using a Population of Phantoms and Clinical Data. . |
| Files in This Item: | There are no files associated with this item. | |||||
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