Imaging Platform for Ophthalmology Data Management

Flywheel offers a comprehensive imaging platform tailored for ophthalmology research, enabling effective data curation and management. It provides researchers with automated pipelines for data curation, a built-in viewer, and preprocessing algorithms. These capabilities accelerate the extraction of insights from ophthalmology data.

The platform supports streamlined workflows and allows for the harmonization of data from varied locations. It assists in validated research for clinical trials and AI development, offering an end-to-end solution for medical imaging needs.

Key benefits of using this platform include:

• Resource savings through remote data uploading and sharing.
• Data curation, classification, and conversion to DICOM format.
• Integration of diverse imaging and video data formats.
• Secure data access on a HIPAA-compliant platform.
• Accelerated workflows through ophthalmology-specific algorithms.
• Audit readiness with 21 CFR Part 11 compliance.

Many pharmaceutical companies utilize Flywheel to improve efficiency in annotation campaigns necessary for AI development, reducing campaign timelines significantly and saving up to 90% in costs by centralizing and automating data workflows.

In clinical research, the platform's advanced annotation capabilities allow for qualitative and quantitative assessment of images such as color fundus and OCT, essential for comprehensive studies. It enables consistent and standardized data handling through features like 2+1 adjudication paradigms and supports various imaging modalities.

Flywheel also empowers collection and centralization of imaging data from multiple sources, supporting retinal imaging formats such as optical coherence tomography, fundus photography, and fluorescein angiography. It converts data from devices like Zeiss and Heidelberg into DICOM, and conducts automated QA of OCT images.

The platform includes a specialized viewer with tools tailored for ophthalmology, such as an interactive ETDRS grid and retinal annotation features, and supports video data management with CVAT integration. Researchers can also design and customize reader protocols directly within the platform, enhancing the efficiency of annotation workflows.