Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866929310709841920 |
|---|---|
| author | Kulkarni, Pranav Kanhere, Adway Kukreja, Harshita Zhang, Vivian Yi, Paul H. Parekh, Vishwa S. |
| author_facet | Kulkarni, Pranav Kanhere, Adway Kukreja, Harshita Zhang, Vivian Yi, Paul H. Parekh, Vishwa S. |
| contents | Generative Adversarial Network (GAN)-based synthesis of fat suppressed (FS) MRIs from non-FS proton density sequences has the potential to accelerate acquisition of knee MRIs. However, GANs trained on single-site data have poor generalizability to external data. We show that federated learning can improve multi-center generalizability of GANs for synthesizing FS MRIs, while facilitating privacy-preserving multi-institutional collaborations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_07374 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning Kulkarni, Pranav Kanhere, Adway Kukreja, Harshita Zhang, Vivian Yi, Paul H. Parekh, Vishwa S. Image and Video Processing Computer Vision and Pattern Recognition Machine Learning Generative Adversarial Network (GAN)-based synthesis of fat suppressed (FS) MRIs from non-FS proton density sequences has the potential to accelerate acquisition of knee MRIs. However, GANs trained on single-site data have poor generalizability to external data. We show that federated learning can improve multi-center generalizability of GANs for synthesizing FS MRIs, while facilitating privacy-preserving multi-institutional collaborations. |
| title | Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning |
| topic | Image and Video Processing Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2404.07374 |