TrueFidelity™ GSI images

TrueFidelity- Deep Learning Image Reconstruction

Introducing a new era of image reconstruction.

TrueFidelity images on a BMI 62 patient (400 lbs, 1.73 m)

Where deep learning does its learning matters.

A deep learning image reconstruction application is only as good as the training it receives. GE Healthcare trained its reconstruction engine using a library of thousands of low noise, filtered back projection (FBP) images—considered the gold standard of image quality.

    Confidence. Not compromise.

    Compared with even the most sophisticated Model-Based Iterative Reconstruction, TrueFidelity CT Images are scanning taken to another level. Contrast visualization is maintained, noise and artifacts are minimized, edges are maintained—just enough—so there’s remarkable clarity and none of the compromise that comes with unfamiliar noise texture.1


    The voice of customers


    Dhiraj Baruah, MD Froedtert & the Medical College of Wisconsin "Reduced noise in deep learning cardiac imaging allows for reduction in kVp while maintaining image quality."

    See for Yourself

    For current Revolution CT users: Contact your GE Healthcare representative to see your own images reconstructed using TrueFidelity.
    It's time to get a closer look at a better way of seeing. Learn more about GE Healthcare's TrueFidelity Images.


    1. As demonstrated in a clinical evaluation consisting of 60 cases and 9 physicians, where each case was reconstructed with both DLIR and ASiR-V and evaluated by 3 of the physicians. In 100% of the reads, DLIR's image sharpness was rated the same as or better than ASiR-V's. In 91% of the reads, DLIR's noise texture was rated better than ASiR-V's. This rating was based on each individual reader's preference.