Rehman, Muhammad Habib Ur;
Hugo Lopez Pinaya, Walter;
Nachev, Parashkev;
Teo, James T;
Ourselin, Sebastin;
Cardoso, M Jorge;
(2023)
Federated learning for medical imaging radiology.
The British Journal of Radiology
, 96
(1150)
, Article 20220890. 10.1259/bjr.20220890.
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Abstract
Federated learning (FL) is gaining wide acceptance across the medical AI domains. FL promises to provide a fairly acceptable clinical-grade accuracy, privacy, and generalisability of machine learning models across multiple institutions. However, the research on FL for medical imaging AI is still in its early stages. This paper presents a review of recent research to outline the difference between state-of-the-art [SOTA] (published literature) and state-of-the-practice [SOTP] (applied research in realistic clinical environments). Furthermore, the review outlines the future research directions considering various factors such as data, learning models, system design, governance, and human-in-loop to translate the SOTA into SOTP and effectively collaborate across multiple institutions.
| Type: | Article |
|---|---|
| Title: | Federated learning for medical imaging radiology |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1259/bjr.20220890 |
| Publisher version: | https://doi.org/10.1259/bjr.20220890 |
| Language: | English |
| Additional information: | Copyright © 2023 The Authors. Published by the British Institute of Radiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Brain Repair and Rehabilitation |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10179961 |
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