FDA Radiology AI Devices

The Swoop Portable MR Imaging System by Hyperfine is a bedside portable MRI device designed to produce images of the internal structure of the head. It uses magnetic resonance imaging with advanced image reconstruction algorithms that include deep learning to enhance image quality by reducing noise and blurring. This helps clinicians obtain diagnostic images even when full diagnostic examination is not practical, aiding diagnosis at the point of care in facilities such as emergency and critical care units.

The uMR 680 is a 1.5 Tesla superconducting magnetic resonance imaging (MRI) system designed to produce diagnostic-quality images of the head, body, and extremities. It includes a deep-learning based image processing algorithm called DeepRecon for image denoising and super-resolution, enhancing image quality and assisting clinicians in diagnosis.

The SIGNA Victor is a 1.5 Tesla whole body MRI scanner designed to provide high-resolution diagnostic images quickly and with a high signal-to-noise ratio. It produces images in multiple planes and supports imaging of the entire body, including brain, spine, joints, heart, abdomen, and more, aiding clinicians in diagnosing a variety of conditions.

MR Diffusion Perfusion Mismatch V1.0 by Olea Medical is an AI-powered software tool that automatically processes MR Diffusion and Perfusion imaging data to compute parametric maps, extract volume metrics, and calculate mismatch volumes. It assists radiologists and surgeons by providing quantitative imaging data that supports clinical decision-making. The software integrates with medical image platforms to streamline workflow without altering the original images and is intended to be used alongside other clinical information, not as a standalone diagnostic tool.

The MR 5300 and MR 7700 R11 MR Systems by Philips are advanced magnetic resonance imaging (MRI) devices that provide high-quality images of the internal structures of the head, body, or extremities. These systems help clinicians by enabling detailed visualization, which supports diagnosis, therapy planning, and interventional procedures. The devices incorporate updated software (R11) and minor hardware enhancements, including AI-powered SmartSpeed features that improve image acquisition and reconstruction, facilitating faster and more accurate MRI scans.

BrainInsight is an automated software that processes low-field MRI brain images to provide automatic labeling, spatial measurement, and volumetric quantification of brain structures. It produces annotated and segmented brain images with color overlays and detailed reports, helping clinicians assess brain anatomy and abnormalities efficiently, particularly using low-field MRIs.

The Swoop Portable MR Imaging System by Hyperfine is a bedside MRI device that allows clinicians to capture magnetic resonance images of the head without moving the patient. It utilizes advanced deep learning-based image reconstruction to improve image quality, reducing noise and blurring. This portable device helps provide timely diagnostic information in critical care settings where traditional MRI is difficult.

The Avenda Health AI Prostate Cancer Planning Software is an AI-driven tool that assists physicians by segmenting prostate MR images, evaluating and quantifying lesions, and planning diagnostic or interventional procedures such as biopsies or tissue ablation. It provides a cancer probability map and confidence scores to help clinicians accurately characterize prostate cancer lesions, improving workflow efficiency and decision making in prostate cancer care.

The SIS System version 5.6.0 is a medical imaging software that helps surgeons, neurologists, and radiologists visualize specific brain structures in 3D to assist with planning neurological surgeries such as deep brain stimulation. It uses advanced image processing and machine learning techniques to create patient-specific anatomical models from MRI and CT images, improving precision during surgical interventions.

BoneMRI v1.4 is an image processing software that analyzes 3D gradient echo MRI scans to enhance visualization of bone structures in the pelvic and lumbar spine regions. It uses a convolutional neural network algorithm to generate images with improved bone contrast compared to surrounding soft tissue, helping clinicians better assess bone morphology and density without the need for CT scans. It is intended for use by radiologists and orthopedic surgeons to aid in image interpretation, but not for tumor diagnosis.