Flywheel for oncology research

A medical imaging platform for oncology data management

Flywheel gives researchers tools to manage oncology imaging at scale, unite multimodal data, and easily create training datasets. Find out how Flywheel is accelerating AI development for rapid tumor detection, segmentation, and improved cancer treatment.

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Accelerate your cancer image analysis

Flywheel is a medical imaging data and AI platform that supports oncology researchers at healthcare institutions and life sciences enterprises around the world. Flywheel helps researchers manage imaging and associated data, scale up quickly to support AI/ML workflows, and maintain compliance in collaborations.

  • Robust viewer features; streamlined annotation and tumor segmentation
  • Blinded reader workflows and task management
  • Customizable de-identification
  • Support for multimodal data
  • Ready-made Gears—standardized plug-in applications—to automate routine tasks and workflows
  • Extensible by design, with open architecture for access by any platform

Webinar: Medical Imaging in R&D — Streamlining Reader Workflows

Administering reader workflows—assigning oncology images to readers, adjudicating the resulting data, and keeping this work efficient and compliant—is no simple feat, particularly at the scale necessary for machine learning. See how Flywheel allows researchers to design their own custom, compliant workflows that guide readers through their tasks efficiently.

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Streamlined Oncology Data Management at an Imaging Core

An oncology research center utilized Flywheel in its preclinical imaging core to store research data for labs using a variety of imaging modalities, including MR, CT, and PET. Flywheel allowed researchers to centralize and standardize their data, accelerating their precision medicine research, which combines molecular imaging, imaging biomarkers, and biological data.

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Oncology data management features

  • Automate image ingestion and curation
  • Simplify reader studies and task management
  • Prepare data for complex analysis and AI
  • Collaborate between disciplines, institutions, and enterprises
  • Unite modalities to support cutting-edge research
  • Easily index enterprise data and create cohorts
  • Automate provenance
  • Turn imaging archives into analysis-ready datasets

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