Author

Mehrtash Harandi

2 papers indexed here

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Open access Aug 2026

Segment any tumour: an uncertainty-aware vision foundation model for whole-body analysis

Prompt-driven vision foundation models, such as the Segment Anything Model, have shown adaptability in computer vision, but their use in medical imaging remains challenging due to heterogeneous anatomy, artefacts, and low-contrast tumour boundaries. This is particularly difficult in whole-body tumour analysis, where mo...

Himashi Peiris, Si-Zhe Wang, Gary F. Egan et al. · Nature Communications · 2 citations

#machine learning Preprint Sep 2026

Open Vocabulary Domain Unlearning

This work formalizes Open-Vocabulary Domain Unlearning (OVDU), a rigorous protocol that mandates domain forgetting must transfer to held-out classes and proposes a surgical parameter-editing framework that vastly improves open-vocabulary generalization over existing baselines.

Sumanth Udupa, Mehrtash Harandi, Ya-Dan Luo et al. · 0 citations