Standout Papers

Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation 2023 2026 202496
  1. Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation (2023)
    Krishna Chaitanya, Ertunç Erdil et al. Medical Image Analysis

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Citing Papers

Segment anything model for medical image segmentation: Current applications and future directions
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Source-free unsupervised domain adaptation: A survey
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1 intermediate paper

Works of Ertunç Erdil being referenced

Test-time adaptable neural networks for robust medical image segmentation
2020

Author Peers

Author CVPR Artificial Intelligence Media Technology RNMI Last Decade Papers Cites
Ertunç Erdil 165 156 18 92 13 296
I‐Hsuan Hong 3 16 33 745
Ana L. M. Batista de Carvalho 1 5 19 41 539
Vladimir Matić 11 6 17 26 296
Brian Handly 26 14 386
Sara Moutinho 23 460

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2026