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Flywheel
The Medical Imaging Data Management and Analysis Platform

What is Flywheel?

Flywheel provides a comprehensive platform dedicated to the management and analysis of medical imaging data. It enables leading researchers and healthcare organizations to accelerate their work and foster innovation by simplifying data management processes. The platform offers tools to securely handle large volumes of imaging data, automate critical research workflows, and scale according to user requirements, ultimately maximizing the value derived from medical imaging assets. It addresses the significant time typically spent by data scientists on finding, curating, and organizing data by automating these tasks.

Specifically designed for life science R&D, clinical researchers, and AI developers, Flywheel facilitates the secure discovery, management, curation, and computation of extensive datasets. This empowers users within organizations or collaborative groups across the globe to focus on breakthroughs rather than data logistics. The platform supports the creation of analysis-ready datasets crucial for research and AI development, offering an extensible solution for managing complex medical imaging information efficiently and securely.

Features

  • Data Discovery: Tools for locating relevant medical imaging data.
  • Data Curation: Functionality for organizing and preparing imaging datasets.
  • Automated Workflows: Streamlines research processes by automating repetitive tasks.
  • Secure Collaboration: Enables secure sharing of data within and between organizations.
  • Scalable Architecture: Platform designed to handle growing data volumes and user needs.
  • AI Development Support: Facilitates the creation of analysis-ready datasets and algorithm development.
  • Flywheel Gears: Open-source plug-ins to automate specific tasks.
  • Expert Guidance: Access to Scientific Solutions Engineers for consultation and training.

Use Cases

  • Accelerating drug development in pharmaceutical R&D.
  • Streamlining data management for clinical research studies.
  • Developing and training AI models for medical image analysis.
  • Managing and sharing data for multi-site clinical trials.
  • Automating image processing workflows for therapeutic applications.
  • Enhancing oncology imaging research.
  • Supporting the development of personalized healthcare solutions.
  • Facilitating medical device development using imaging data.
  • Managing expert annotation projects for medical images.
  • Validating and standardizing imaging workflows across institutions.

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