Advances in foundation modeling have reshaped computational pathology. However, the increasing number of available models and lack of standardized benchmarks make it increasingly complex to assess their strengths, limitations, and potential for further development. To address these challenges, we introduce a new suite of software tools for whole-slide image processing, foundation model benchmarking, and curated publicly available tasks. We anticipate that these resources will promote transparency, reproducibility, and continued progress in the field.
Accelerating Data Processing and Benchmarking of AI Models for Pathology
A new suite of software tools addresses the challenges of benchmarking foundation models in computational pathology by providing processing tools and curated tasks for whole-slide images.
- Year
- 2025
- Venue
- arXiv 2025
- Authors
- 5
- Hosting
- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2502.06750ARXIV-DEFAULT
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