FDA Radiology AI Devices

SIGNA MAGNUS is a high-performance, head-only 3.0T magnetic resonance imaging (MRI) system designed to capture detailed images of the head, neck, TMJ, and limited cervical spine. It supports various imaging planes and advanced diffusion techniques to produce high-resolution images that assist physicians in diagnosis, helping improve patient care through better imaging quality and shorter scan times.

Sonic DL is a software feature by GE Healthcare that uses deep learning to reconstruct cardiac MR images much faster by processing under-sampled data. It allows highly accelerated imaging with preserved image quality, enabling faster and more efficient MRI scans for cardiac assessment in patients of all ages.

AIR Recon DL is a deep learning-based software feature for GE Healthcare MRI systems that improves image quality by reducing noise and ringing artifacts in MRI images. It helps clinicians by enabling shorter scan times without losing image clarity, thus improving patient comfort and diagnostic accuracy across multiple anatomies and MR field strengths.

Deep Learning Image Reconstruction (DLIR) by GE Medical Systems is an AI-powered CT image reconstruction method that uses a deep neural network to produce high-quality cross-sectional images of the head and whole body. It supports multiple CT acquisition types and enhances image quality by reducing noise and artifacts, helping clinicians get clearer and more accurate imaging results.

The Discovery MI Gen2 is a PET/CT imaging system by GE Medical Systems designed to produce detailed attenuation-corrected PET images combined with CT scans. It helps clinicians by providing anatomically localized images of radiopharmaceutical distribution, aiding diagnosis, treatment planning, and monitoring of diseases such as cancer, neurological disorders, and cardiac conditions across various body regions.

The SIGNA 7.0T is a high-performance whole-body magnetic resonance imaging (MRI) system designed to produce high-resolution images with high signal-to-noise ratio and short scan times. It supports imaging of the head and extremities in multiple planes and includes AI-driven image reconstruction software called AIR Recon DL, which enhances image quality by improving signal-to-noise ratio and sharpness without compromising low contrast detectability. This aids clinicians by providing clearer images for more accurate diagnoses.

MaxFOV 2 is a software option for GE CT scanners that uses deep learning to extend the display field of view in CT images beyond the scanner's nominal field, providing improved visualization of patient anatomy, especially useful in radiation therapy planning and for large patients. This helps clinicians obtain more complete images for diagnosis and treatment planning when parts of the body are outside standard scan coverage.

Deep Learning Image Reconstruction for Gemstone Spectral Imaging by GE Medical Systems is an AI-powered CT image reconstruction method designed to produce high-quality cross-sectional CT images from dual-energy X-ray data. It is intended for whole body, vascular, and contrast-enhanced head CT applications, enhancing image quality with a deep neural network-based algorithm that improves low contrast detectability, noise reduction, and artifact suppression, supporting accurate and reliable diagnosis.

The SIGNA 7.0T is a high-performance whole-body MRI scanner designed by GE Healthcare to produce high-resolution images of the head and extremities. It supports multiple imaging techniques and pulse sequences to generate detailed anatomical, functional, spectroscopic, and vascular images. The device helps clinicians in diagnosis by delivering high signal-to-noise ratio images with shorter scan times, particularly enabled by its advanced 7.0 Tesla magnetic field strength and optimized hardware.

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.