FDA Radiology AI Devices

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 Revolution Ascend is a CT scanner designed to generate detailed cross-sectional images of various body parts including the head, whole body, cardiac, and vascular areas. It uses x-ray transmission data taken at different angles and planes. The device supports multiple acquisition modes and post-processing of images, aiding clinicians in diagnosing disease, trauma, and abnormalities, as well as planning and monitoring therapy.

SIGNA Hero is a whole body 3.0 Tesla MRI scanner from GE Healthcare that supports high resolution images with a high signal-to-noise ratio and short scan times. It produces detailed images of structures and functions throughout the body to aid physicians in diagnosis by providing axial, sagittal, coronal and oblique images, along with spectroscopic and dynamic imaging capabilities.

SIGNA Prime is a whole body magnetic resonance imaging (MRI) scanner that supports high resolution and fast scan times. It produces detailed images and spectroscopic data of various body regions, helping clinicians diagnose a wide range of conditions by showing the spatial distribution and molecular environment of tissues.

Precise Image is an AI-powered reconstruction software for computed tomography (CT) systems developed by Philips. It produces high-quality images with lower radiation dose and noise, improving the detectability of low contrast features. This helps clinicians obtain clearer diagnostic images from CT scans of the head, body, and vascular regions, enhancing patient safety by reducing radiation exposure while maintaining image quality.

The Vantage Fortian 1.5T, MRT-1550, V8.0 with AiCE Reconstruction Processing Unit for MR is a 1.5 Tesla MRI system that produces detailed cross-sectional images of the body or head. It incorporates AI-based reconstruction and machine learning technologies to enhance image quality and assist in planning scans, improving diagnostic accuracy and patient comfort.

The Swoop Point-of-Care Magnetic Resonance Imaging (POC MRI) System by Hyperfine, Inc. is a portable MRI device designed to provide bedside imaging of the brain. It uses advanced deep learning for image reconstruction to reduce noise and blurring, enabling clinicians to view internal head structures more clearly. This system facilitates quicker and more accessible brain imaging in various care settings, aiding in diagnosis without the need to transport patients to traditional MRI suites.

Deep Learning Image Reconstruction by GE Healthcare is a software that uses deep neural networks to reconstruct high-quality CT images from X-ray transmission data. It helps radiologists by producing images with improved noise reduction, spatial resolution, and artifact suppression, suitable for head, whole body, cardiac, and vascular CT scans at routine clinical throughput.

RayStation 11.0 is a software system used in radiation therapy and medical oncology for planning, analyzing, and administering treatment plans. It helps clinicians design and optimize radiation treatments accurately based on the patient's medical imaging data, enhancing treatment effectiveness and safety.

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.