PathML
An open-source toolkit for scalable, standardized computational pathology analysis, enabling AI and machine learning on large imaging datasets.
What is PathML?
PathML is an open-source toolkit for computational pathology that provides tools to process, analyze, and apply machine learning to large-scale pathology imaging datasets. It addresses the challenges of scalability and standardization in digital pathology, enabling researchers to derive insights from complex cancer imaging data.
Pathology researchers, computational biologists, and data scientists working with whole-slide images who need scalable pipelines for preprocessing, analysis, and AI model development.
Developers choose PathML for its comprehensive, standardized framework that simplifies complex workflows, supports a wide range of image formats, and integrates seamlessly with popular ML libraries, accelerating research in computational pathology.
Overview
Tools for computational pathology
Use Cases
Best For
- Processing and analyzing whole-slide images for cancer research
- Building standardized preprocessing pipelines for pathology AI models
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