| Title |
Independent attenuation correction of whole body [18F]FDG-PET using a deep learning approach with Generative Adversarial Networks
|
|---|---|
| Published in |
EJNMMI Research, May 2020
|
| DOI | 10.1186/s13550-020-00644-y |
| Pubmed ID | |
| Authors |
Karim Armanious, Tobias Hepp, Thomas Küstner, Helmut Dittmann, Konstantin Nikolaou, Christian La Fougère, Bin Yang, Sergios Gatidis |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 51 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 20% |
| Researcher | 8 | 16% |
| Student > Bachelor | 3 | 6% |
| Professor | 2 | 4% |
| Lecturer > Senior Lecturer | 2 | 4% |
| Other | 7 | 14% |
| Unknown | 19 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 8 | 16% |
| Computer Science | 6 | 12% |
| Medicine and Dentistry | 6 | 12% |
| Physics and Astronomy | 3 | 6% |
| Neuroscience | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 22 | 43% |