Slideflow framework
Open-source Python package, MIT-licensed, that gives researchers one API for building and testing deep-learning models for histopathology on TensorFlow/Keras or PyTorch, covering whole-slide image processing, model training with uncertainty quantification, multiple-instance learning, self-supervised learning, GANs, saliency maps, heatmaps and a live visualization studio.
Find alternatives to Slideflow framework
What it does
- Medical imaging analysis
- Model training
Features 3
- Training pipelinesCustomizable model training with uncertainty quantification.
- Whole-slide processingTools for efficient whole-slide image processing.
- InterpretabilityPredictive heatmaps, mosaic maps, GANs and saliency maps.
Sources
- Pricing
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Official documentation · 20 Oct 2026
Home page: the Slideflow framework is MIT-licensed and open source on GitHub.
- Description
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Official documentation · 20 Oct 2026
Documentation: "Slideflow is a Python package that provides a unified API for building and testing deep learning models for histopathology".
- What it does
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Official documentation · 20 Oct 2026
Documentation: "Slideflow is a Python package that provides a unified API for building and testing deep learning models for histopathology".
- Sold within
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Official documentation · 20 Oct 2026
Home page: the framework is MIT-licensed and open on GitHub; no sales contact is needed.
- Name
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Official documentation · 20 Oct 2026
Name as published on the product page.
- URL
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Official documentation · 20 Oct 2026
Product page, read 2026-10-20.
- Deployment
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Official documentation · 20 Oct 2026
Documentation and home page: a Python package installed and run by the user; the home page links the GitHub repository.
- Interfaces
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Official documentation · 20 Oct 2026
Documentation and home page: a Python package installed and run by the user; the home page links the GitHub repository.
Also from Slideflow Labs
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Slideflow AI biomarker tests Application
AI biomarker tests for cancer pathology that run as isolated single-tenant containers in a dedicated cloud environment for the hospital: the lab scans the H&E slide it already prepares, deep-learning models read quantitative tumour biology from it, and a structured biomarker output returns to the treating physician through the hospital's clinical reporting workflow in minutes; the site marks it for research and clinical evaluation use and no price is published.
Open Slideflow Labs in the directory
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