Federated Learning of Generative Image Priors for MRI Reconstruction

• Published in: IEEE transactions on medical imaging Vol. 42; no. 7; pp. 1996 - 2009
• Main Authors: Elmas, Gokberk, Dar, Salman U. H., Korkmaz, Yilmaz, Ceyani, Emir, Susam, Burak, Ozbey, Muzaffer, Avestimehr, Salman, Cukur, Tolga
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: accelerated; Adaptation models; Biological system modeling; collaborative; Data models; Deep Learning; distributed; Explicit knowledge; Federated learning; generative; Humans; Image processing; Image Processing, Computer-Assisted - methods; Image quality; Image reconstruction; Knowledge acquisition; Learning; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; MRI; Operators; Performance enhancement; prior; Privacy; reconstruction; Training

Multi-institutional efforts can facilitate training of deep MRI reconstruction models, albeit privacy risks arise during cross-site sharing of imaging data. Federated learning (FL) has recently been introduced to address privacy concerns by enabling distributed training without transfer of imaging d...