1 citations · 1 across the 4 of their papers we have counts for
4 papers
Understanding the Transfer Limits of Vision Foundation Models
Shiqi Huang, Yipei Wang, Natasha Thorley +8
Foundation models leverage large-scale pretraining to capture extensive knowledge, demonstrating generalization in a wide range of language tasks. By comparison, vision foundation…
Impact of Clinical Image Quality on Efficient Foundation Model Finetuning
Yucheng Tang, Pawel Rajwa, Alexander Ng +11
Foundation models in medical imaging have shown promising label efficiency, achieving high performance on downstream tasks using only a fraction of the annotated data otherwise req…
Promptable cancer segmentation using minimal expert-curated data
Lynn Karam, Yipei Wang, Veeru Kasivisvanathan +3
Automated segmentation of cancer on medical images can aid targeted diagnostic and therapeutic procedures. However, its adoption is limited by the high cost of expert annotations r…
T2-Only Prostate Cancer Prediction by Meta-Learning from Bi-Parametric MR Imaging
Weixi Yi, Yipei Wang, Natasha Thorley +6
Current imaging-based prostate cancer diagnosis requires both MR T2-weighted (T2w) and diffusion-weighted imaging (DWI) sequences, with additional sequences for potentially greater…