Deep Learning Image Reconstruction
GE Medical Systems, LLC.Deep Learning Image Reconstruction by GE Medical Systems is a software option for CT scanners that uses a dedicated deep neural network to generate high-quality cross-sectional images of the head and whole body from X-ray transmission data. It improves image quality while maintaining noise performance and spatial resolution, supporting routine clinical workflows for head, whole body, cardiac, and vascular CT scans across all ages.
Intended Use
The Deep Learning Image Reconstruction option is a deep learning based reconstruction method intended to produce cross-sectional images of the head and whole body by computer reconstruction of X-ray transmission data taken at different angles and planes, including Axial, Helical (Volumetric), and Cardiac acquisitions, for all ages.
Technology
Uses a dedicated Deep Neural Network (DNN) trained specifically on Revolution CT systems to reconstruct CT images that have appearance similar to traditional filtered back projection images, while maintaining ASiR-V performance in noise, low contrast detectability, spatial resolution, and artifact suppression.
Performance
Bench testing compared image quality metrics (low contrast detectability, image noise, spatial resolution, artifact suppression, etc.) between Deep Learning Image Reconstruction and predicate ASiR-V on identical raw datasets from Revolution CT. Clinical testing involved 60 retrospective cases assessed by 9 radiologists for image quality and diagnostic use, showing that Deep Learning Image Reconstruction is as safe and effective as the predicate device.
Predicate Devices
No predicate devices specified
Device Timeline
- 1
Submission
11/19/2018
4 months - 2
FDA Approval
4/12/2019
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