构建病理图像处理与模型评测工具集，提升研究透明度与可复现性。
Accelerating Data Processing and Benchmarking of AI Models for Pathology
- 开发全切片图像处理与基础模型评测的软件工具套件
- 提供公开可用的标准化任务与基准测试数据集
- 适合从事数字病理与AI模型评估的研究人员使用
基础模型的发展重塑了计算病理学。然而，模型数量激增且缺乏标准化评测基准，使得评估其优势、局限及发展潜力变得愈发复杂。为此，我们提出一套新的软件工具，涵盖全切片图像处理、基础模型评测以及经筛选的公开可用任务。这些资源有望推动该领域的透明性、可复现性与持续进步。
原文摘要 · Abstract (English)
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.
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