Develop Medical Imaging AI at Scale

Flywheel allows you to develop, test and verify imaging models in your preferred environments, and ensure that all versions and results can be found alongside your source data. Pull analysis-ready data sets for training and testing into the AI development tools you already know and use.

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Unleash Image-Augmented Model Development

  • Curate and feed data into your machine learning infrastructure for training and AI development
  • Clinical Research and Imaging Research Icon
    Explore and verify algorithms with Jupyter Notebooks tied to your projects
  • Compute, AI Developers and Machine Learning Icon
    Develop production-grade AI applications at scale, using integrations with Microsoft Azure Machine Learning Studio & NVIDIA AI Enterprise
  • Life Sciences Icon
    Publish and share models that pass quality metrics, to enable reproducibility and eliminate redundant model building
  • AI Developers and Machine Learning Icon
    Assign images to external readers, adjudicate results, and fine-tune model accuracy

One Platform for Data Discovery, Aggregation, Curation and Training

UW-Madison researchers harnessed the power of Flywheel and NVIDIA Healthcare to enhance patient outcomes and reduce manual data processing work from eight months, down to one day.

See How

A Suite of Tools for
Machine Learning in Medical Imaging

Find Ground Truth Data

Normalize & Enrich

  • Run integrated medical image processing algorithms to normalize & curate datasets
  • Develop containerized Gears and import existing pipelines to accelerate workflows
  • Bring your curated data to preloaded, versioned MONAI containers at the project level, through NVIDIA AI Enterprise
  • Access data in Azure ML Studio workspaces for cloud-scale enrichment

Train & Test

  • Package and test algorithms iteratively
  • Leverage cloud compute resources to build model registries
  • Monitor performance and tune hyperparameters
  • Link favorites to Flywheel projects for collaboration and review
  • Tag models with clinical information, including therapeutic area, modality, or anatomy

Deploy to Readers

  • Access centralized reader study management tools, and batch assign cases and user permissions
  • Give experts access to necessary medical information while maintaining blinding
  • Randomize cases, and collect segmentations & labels with custom forms to verify your model is gold standard

Access Data & Model Outputs in One Unified Platform

Azure Machine Learning Studio

Develop machine learning in medical imaging at scale with curated data in an end-to-end platform. Share Azure ML Studio models with collaborators in Flywheel to test across projects and prevent redundant model-building.

NVIDIA AI Enterprise

Experience an end-to-end imaging data management platform with NVIDIA’s model training capabilities at scale. Access a container pre-loaded with MONAI algorithms, ready for you to explore in your environment. Choose from domain-specific algorithms, test & verify them on your data, and make adjustments as needed.

Jupyter Notebooks

Empower developers to explore data, assign machine learning cohorts, and begin experimenting. Write executable code that can access project data, track notebook versions, and organize model results. Distill critical outputs from developed algorithms in a simple UI, and share them with stakeholders.

Gearify Your AI

Publish Gears, the Flywheel plug-in applications that automate routine tasks, including metadata extraction, classification, quality assurance, format conversion, and full analytic pipelines.

See the medical image processing algorithms here

Keep Exploring


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