Pathology foundation models for training-free case retrieval in salivary gland tumors
In pathology, pattern recognition relies on a frame of reference built through extensive training and experience, which may still fall short when encountering rare cancer subtypes. Archives of previously diagnosed tumors often contain relevant precedents, yet identifying the most relevant cases remains challenging. Here we explore whether content-based retrieval with current pathology foundation models facilitates rare cancer diagnostics without any task-specific training. Pathologists can query a digitized archive using a region of interest (ROI) from a whole slide image (WSI) and retrieve morphologically similar cases, along with their ICD-O codes and corresponding WSIs. The ROI can be ...
| Authors | Maximilian J. Roesel, Niklas Kiermeyer, Philipp Keyl et al. |
|---|---|
| Primary category | cs.CV |
| Published | 15 October 2026 |
| Last updated at source | 15 October 2026 |
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