A

Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation

arXiv (Cornell University)

Abstract

Purpose: To present and evaluate Dafne (deep anatomical federated network), a freely available decentralized, collaborative deep learning system for the semantic segmentation of radiological images through federated incremental learning. Materials and Methods: Dafne is free software with a client-server architecture. The client side is an advanced user interface that applies the deep learning models stored on the server to the user's data and allows the user to check and refine the prediction. Incremental learning is then performed at the client's side and sent back to the server, where it is integrated into the root model. Dafne was evaluated locally, by assessing the performance gain across model generations on 38 MRI datasets of the lower legs, and through the analysis of real-world usage statistics (n = 639 use-cases). Results: Dafne demonstrated a statistically improvement in the accuracy of semantic segmentation over time (average increase of the Dice Similarity Coefficient by 0.007 points/generation on the local validation set, p < 0.001). Qualitatively, the models showed enhanced performance on various radiologic image types, including those not present in the initial training sets, indicating good model generalizability. Conclusion: Dafne showed improvement in segmentation quality over time, demonstrating potential for learning and generalization.

Authors 14

  1. University of Basel · University Hospital of Basel · Department of Biomedicine Basel

    Affiliation as printed

    . Basel Muscle MRI , Department of Biomedical Engineering , University of Basel , Basel , Switzerland

    . Department of Radiology , University Hospital Basel , Basel , Switzerland

  2. University Hospital of Basel

    Affiliation as printed

    . Department of Radiology , University Hospital Basel , Basel , Switzerland

  3. University of Pavia

    Affiliation as printed

    . Department of Mathematics , University of Pavia , Pavia , Italy

  4. University of Basel · University Hospital of Basel · Department of Biomedicine Basel

    Affiliation as printed

    . Basel Muscle MRI , Department of Biomedical Engineering , University of Basel , Basel , Switzerland

    . Department of Radiology , University Hospital Basel , Basel , Switzerland

  5. Leiden University Medical Center

    Affiliation as printed

    . Department of Neurology , Leiden University Medical Center , Leiden , The Netherlands

  6. Leiden University Medical Center

    Affiliation as printed

    . C.J. Gorter MRI Center , Department of Radiology , Leiden University Medical Center , Leiden , The Netherlands

  7. Peking Union Medical College Hospital

    Affiliation as printed

    . Peking Union Medical College Hospital , Beijing , China

  8. University of Basel · University Hospital of Basel · Department of Biomedicine Basel

    Affiliation as printed

    . Basel Muscle MRI , Department of Biomedical Engineering , University of Basel , Basel , Switzerland

    . Department of Radiology , University Hospital Basel , Basel , Switzerland

  9. Istituti Clinici Scientifici Maugeri

    Affiliation as printed

    . Istituti Clinici Scientifici Maugeri IRCCS , Servizio di Diagnostica per Immagini -Istituto di Montescano , Italy

  10. Fondazione Istituto Neurologico Nazionale Casimiro Mondino

    Affiliation as printed

    . Advanced imaging and radiomics center , Neuroradiology Department , IRCCS Mondino Foundation , Pavia , Pavia , Italy

  11. New York University

    Affiliation as printed

    . Department of Radiology , NYU Grossman School of Medicine , New York , NY , USA

  12. Stanford Medicine · Stanford University

    Affiliation as printed

    . Department of Electrical Engineering , Stanford University , Stanford CA , USA

    . Department of Radiology , Stanford University , Stanford , CA , USA

Cited by 20 stored of 20

20 results

No patents citing this paper on Lens.org (checked 2026-10-11).

References 0