FL-MRCM
importedsoftware/fl-mrcm
Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/guopengf/FL-MRCM
- Documentation
- unknown
- Tags
- deep-learning · federated-learning · pytorch
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- Clustered-FL-BrainAGEfederated-learning · pytorch
Official implementation of paper "Brain Age Estimation Using Structural MRI: A Clustered Federated Learning Approach"
- federated_hefederated-learning · pytorch
Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with…
- FedGATfederated-learning · pytorch
Official implementation of FedGAT: Generative Autoregressive Transformers for Model-Agnostic Federated MRI Reconstruction (https://arxiv.org/abs/2502.04521)
- pFLSynthfederated-learning · pytorch
One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis (pFLSynth)
- ECG-with-XAIfederated-learning
Code for CNNs based Explainable arrhythmia detection in federated settings
- FLIPfederated-learning
Federated Learning Interoperability Platform
- api.github.com/repos/guopengf/FL-MRCMretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2022-06-15, 46 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/25.json→ .entries["fl-mrcm"]
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