Name
Title | ||
|---|---|---|
SegSRGAN: Super-resolution and segmentation using generative adversarial networks - Application to neonatal brain MRI. |
Abstract | ||
|---|---|---|
•End-to-end joint super-resolution and segmentation of 3D brain MRI data.•Comprehensive method evaluation on both research and clinical datasets.•Open-source software with detailed implementation description, available on Github.com. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.compbiomed.2020.103755 | Computers in Biology and Medicine |
Keywords | DocType | Volume |
Super-resolution,Segmentation,3D generative adversarial networks,Neonatal brain MRI,Cortex | Journal | 120 |
ISSN | Citations | PageRank |
0010-4825 | 3 | 0.38 |
References | Authors | |
0 | 10 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Quentin Delannoy | 1 | 3 | 0.38 |
| Chi-Hieu Pham | 2 | 19 | 1.53 |
| Clément Cazorla | 3 | 3 | 0.38 |
| Carlos Tor-Díez | 4 | 9 | 1.19 |
| Guillaume Dollé | 5 | 3 | 0.38 |
| Hélène Meunier | 6 | 8 | 0.85 |
| Nathalie Bednarek | 7 | 10 | 2.22 |
| Ronan Fablet | 8 | 312 | 47.04 |
| Nicolas Passat | 9 | 469 | 46.22 |
| Francois Rousseau | 10 | 121 | 16.81 |