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Clinical & Academic Collaborators

Samra Irshad

Researcher, Augmented Intelligence Lab, Kyung Hee University (mentored)

Kyung Hee University, Korea

Samra Irshad is a researcher in the Augmented Intelligence Lab of Seong Tae Kim at Kyung Hee University, Korea, whom we mentored on robust deep learning for surgical vision. Her work covers robust surgical tool segmentation under realistic visual corruptions — contributing to the SegSTRONG-C challenge and benchmark (IEEE TMI 2026) — as well as abdominal multi-organ segmentation, interpretable multimodal models and adversarial robustness. She received her PhD from Swinburne University of Technology, Australia, with work on retinal image analysis.

Education

  1. PhDSwinburne University of Technology, Australia

Research Collaboration and Funded Projects 1 filter all →

Publications 1 filter all →

SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions--An EndoVis' 24 Challenge

Hao Ding, Yuqian Zhang, Tuxun Lu, Ruixing Liang, Hongchao Shu, Lalithkumar Seenivasan, Yonghao Long, Qi Dou, Cong Gao, Yicheng Leng, Seok Bong Yoo, Eung-Joo Lee, Zijian Wu, Yuxin Chen, Septimiu E. Salcudean, Samra Irshad, Shadi Albarqouni, Seong Tae Kim, Yueyi Sun, An Wang, Long Bai, Hongliang Ren, Ihsan Ullah, Ho-Gun Ha, Attaullah Khan, Hyunki Lee, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Sita Tailor, Ricardo Sanchez-Matilla, Imanol Luengo, Tianhao Fu, Jun Ma, Bo Wang, Marcos Fernández-Rodríguez, Estevao Lima, João L. Vilaça, Negin Ghamsarian, Klaus Schoeffmann, Raphael Sznitman, Mathias Unberath

IEEE Transactions on Medical Imaging, 2026

Journal Q1IF 12.4 Responsible AI Robust surgical tool …
PublisherIEEE TMIPDFBibTeX