FDA Radiology AI Devices

Automatic Anatomy Recognition (AAR) is a software medical device that uses deep learning to automatically identify and contour anatomical structures from CT scans. It is designed to assist technicians and physicians in radiation therapy planning by providing precise contours of organs at risk in the head, neck, and chest areas. This helps improve the accuracy and efficiency of treatment planning for patients undergoing radiation therapy for cancers in these body regions.

AI Segmentation by Varian Medical Systems is a cloud-based AI software tool that segments patient anatomical structures from CT scans to assist radiation therapy treatment planning. It automatically delineates organs at risk in regions such as head and neck, thorax, pelvis, and abdomen, helping radiation therapy professionals by streamlining contouring tasks and integrating with treatment planning systems, though clinicians review and approve the results.

Saige-Q is a software tool that analyzes digital breast mammograms using artificial intelligence to identify exams that may contain suspicious findings suggestive of breast cancer. It helps radiologists prioritize these exams in their worklist, enabling faster review of potentially concerning cases. The tool provides passive notification codes but does not provide diagnostic decisions and supports both full-field digital mammography and digital breast tomosynthesis images.

BriefCase for RibFx is an AI-powered software that assists medical specialists by analyzing chest CT scans to identify and flag cases with three or more acute rib fractures. It provides notifications and low-quality preview images on a desktop application, helping radiologists prioritize and review urgent cases sooner, thereby improving workflow efficiency and patient care.

DV.Target is a software product that uses machine learning algorithms to automatically delineate organs-at-risk on CT images. It supports radiation therapy planning by generating organ contours that clinicians can review and edit in a treatment planning system. The software operates on a server and integrates with clinical workflows through DICOM image routing.

Eclipse II with Smart Noise Cancellation is software that improves digital X-ray images by reducing noise using advanced AI technology. It enhances images acquired with digital radiography systems, helping radiologists see clearer images for better diagnosis of adult and pediatric patients, excluding mammography.

The SIS System (Version 5.1.0) is a medical imaging software that helps surgeons, neurologists, and radiologists visualize specific brain structures such as the subthalamic nuclei and globus pallidus from MRI and CT scans. It uses advanced deep learning models to create 3D anatomical models to aid in stereotactic surgical planning and lead placement, improving visualization and accuracy during procedures.

The MAGNETOM Vida, MAGNETOM Sola, MAGNETOM Lumina, and MAGNETOM Altea are magnetic resonance imaging systems designed to produce detailed cross-sectional images and spectra of the head, body, and extremities. These systems aid clinicians in diagnosis by providing high-quality images and offer specialized features such as interventional imaging support and automated workflows, improving reproducibility and efficiency.

The syngo.CT Lung CAD by Siemens Healthcare GmbH is a software tool designed to assist radiologists in detecting solid and subsolid lung nodules on chest CT scans. It uses advanced AI algorithms based on convolutional neural networks to highlight suspicious areas, reducing the chance of missed nodules. The software integrates with existing medical imaging platforms, improving clinicians' efficiency and accuracy in lung nodule detection, a critical task in lung cancer screening and diagnosis.

The Aquilion ONE (TSX-306A/3) V10.4 with Spectral Imaging System is a whole-body CT scanner that can capture detailed cross-sectional volume images of organs in a single rotation. It uses advanced AI algorithms such as deep convolutional neural networks to improve image quality and reduce noise, helping clinicians to better visualize anatomy and potentially optimize iodinated contrast media use. The spectral imaging system acquires images at different energy levels nearly simultaneously to differentiate tissues and materials, assisting in diagnosis and treatment planning.