Intended Use

An automated image processing software application utilizing deep learning for bone segmentation to facilitate optimized visualization of bone marrow in spectral body and extremity CT images for reviewing traumatic and non-traumatic bone pathologies.

Technology

Deep learning based bone segmentation algorithm that generates fused colored material density images (e.g. water minus hydroxyapatite) overlayed on monochromatic or Virtual Unenhanced spectral CT images. Fully automated image post-processing workflow hosted on GE Edison Health Link platform, providing secondary capture DICOM outputs for clinical review.

Performance

Non-clinical testing included design control, risk management, software and system testing. Engineering bench testing verified accurate bone segmentation using a dataset of 146 retrospective spectral CT exams with ground truth from three board-certified radiologists. Clinical testing involved retrospective case assessments by three expert radiologists, demonstrating additional diagnostic value and increased reader efficiency.

Predicate Devices

No predicate devices specified

Device Timeline

  • 1

    Submission

    11/22/2022

    3 months
  • 2

    FDA Approval

    3/9/2023

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