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20232026
most citedFedGIN: Federated Learning with Dynamic Global Intensity Non-linear Augmentation for Organ Segmentation using Multi-modal Images

2 citations · 5 across the 7 of their papers we have counts for

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eess.IV2025★ 2 cited

Optimizing Federated Learning Configurations for MRI Prostate Segmentation and Cancer Detection: A Simulation Study

Ashkan Moradi, Fadila Zerka, Joeran S. Bosma +7

Purpose: To develop and optimize a federated learning (FL) framework across multiple clients for biparametric MRI prostate segmentation and clinically significant prostate cancer (…