Intended Use

Localization and characterization of thyroid ultrasound images in adult patients referred for ultrasound examination.

Technology

Stand-alone, web-based image processing and reporting software that uses machine learning algorithms to localize suspicious thyroid nodules and classify them according to ACR TI-RADS descriptors. Produces reports reviewed and approved by clinicians. Runs on standard computers with DICOM-compliant ultrasound images as input.

Performance

Clinical performance evaluated in a Multi-Reader Multi-Case (MRMC) study with 18 radiologists reading 600 cases, showing improved reader performance with device aid in localization, lexicon characterization, and TI-RADS agreement. Standalone performance comparable to aided read. Non-clinical software validation and risk analysis done per recognized standards.

Predicate Devices

No predicate devices specified

Device Timeline

  • 1

    Submission

    3/14/2024

    5 months
  • 2

    FDA Approval

    9/9/2024

Other devices from See-Mode Technologies Pte. Ltd.

Ready to Sharpen Your Edge?

Join hundreds of your peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.

We respect your privacy. Unsubscribe at any time.