Develop federated foundation models for medical image segmentation.
(1) A framework for fine-tuning all the parameters of SAM (Segment Anything Model) in the federated learning paradigm for medical image segmentation, called FedSAM.
(2) A framework for fine-tuning MSA (Medical SAM Adapter) in the federated learning paradigm for medical image segmentation, called FedMSA.
Welcome to read our paper, which provides detailed descriptions of the methods and experimental results: FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation
FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation
Yuxi Liu, Guibo Luo*, Yuesheng Zhu* MICCAI2024
If you find this work is helpful to your research, please consider citing our paper:
@article{liu2024fedfms,
title={FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation},
author={Liu, Yuxi and Luo, Guibo and Zhu, Yuesheng},
journal={arXiv preprint arXiv:2403.05408},
year={2024}
}Thanks for your interest in our work!
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Python==3.8.16
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torch==2.0.0
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torchvision==0.15.0
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numpy==1.24.3
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opencv_python==4.7.0.72
See the detail requirements in requirements.txt
run ./run_ft/run_fed_sam_FeTS_ft.sh for federated learning in FeTS2022 Dataset (Brain Tumor).
run ./run_ft/run_fed_sam_fundus_ft.sh for federated learning in Fundus Dataset.
run ./run_ft/run_fed_sam_nuclei_ft.sh for federated learning in Nuclei Dataset.
run ./run_ft/run_fed_sam_prostate_ft.sh for federated learning in Prostate Cancer Dataset.
run ./run_ft/run_fed_sam_ctlung_ft.sh for federated learning in Lung Dataset.
run ./run_fed_sam_FeTS.sh for federated learning in FeTS2022 Dataset (Brain Tumor).
run ./run_fed_sam_fundus.sh for federated learning in Fundus Dataset.
run ./run_fed_sam_nuclei.sh for federated learning in Nuclei Dataset.
run ./run_fed_sam_prostate.sh for federated learning in Prostate Cancer Dataset.
run ./run_fed_sam_ctlung.sh for federated learning in Lung Dataset.
Federated Tumor Segmentation Challenge | FeTS Challenge 2021 (fets-ai.github.io)
REFUGE Challenge Dataset | Papers With Code
Glaucoma Fundus Imaging Datasets | Kaggle
Drishti-GS - RETINA DATASET FOR ONH SEGMENTATION (kaggle.com)
Prostate cANcer graDe Assessment (PANDA) Challenge | Kaggle
MoNuSAC-2020 - Home (biomedicalimaging.org)
Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge - ScienceDirect
Initiative for Collaborative Computer Vision Benchmarking (i2cvb.github.io)