FDA Radiology AI Devices

AIBOLIT 3D+ is a software system that takes CT scan images and processes them into detailed 3D visual models of anatomical structures. This tool helps doctors plan surgeries, train, and educate patients by enabling interactive viewing of organs and tissues from multiple angles and with enhanced clarity. It supports better decision-making and may reduce errors during procedures.

RT-Mind-AI is a software tool designed to automatically segment organs-at-risk in non-contrast CT images for patients undergoing radiation therapy. It helps radiation oncologists by providing accurate anatomical contours that support treatment planning and evaluation, improving workflow and precision.

Al-Rad Companion (Pulmonary) is an AI-powered software by Siemens that processes CT images of the lungs to assist clinicians in quantitatively and qualitatively analyzing lung diseases. It segments lungs and lobes, detects lung lesions and areas of abnormal tissue density, and provides measurements to support radiologists and physicians in emergency, specialty, and general care settings. This helps streamline and improve lung disease evaluation.

Advanced Algorithms for Treatment Management Applications (AATMA) is a software library that uses machine-learning convolutional neural networks to automatically segment medical images. It provides derived data sets for use in radiation therapy treatment planning, accessible via an API and intended to help clinicians efficiently generate and review treatment contours from imaging data.

FlightPlan for Liver is a post-processing software that helps physicians analyze 3D X-ray angiography images to visualize the liver's vasculature and identify arteries near hypervascular lesions. It incorporates AI algorithms, including deep learning-based liver segmentation, to support the planning of liver embolization procedures, improving physician workflow and precision in treatment planning.

Contour ProtégéAI is a software tool that assists trained medical professionals by automatically creating contours on CT and MR medical images using machine-learning algorithms. It helps in quantitative analysis, adaptive therapy, image segmentation of various anatomical regions including prostate via MR images, and supports radiation therapy treatment planning. The contours can be reviewed and edited with appropriate visualization software.

StrokeSENS LVO is software that uses AI to analyze CT angiograms of the head to identify suspected large vessel occlusions, which can cause strokes. It assists healthcare providers by flagging potential LVO cases and sending notifications to specialists in near real-time, helping prioritize urgent cases and improve workflow efficiency. The software does not alter the original images and is intended to be used alongside existing diagnostic workflows.

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.

HealthCCSng is a software device that automatically analyzes non-cardiac-gated CT scans to estimate the amount of calcified plaque in coronary arteries, which can indicate coronary artery disease risk. It provides radiologists with calcium detection categories and annotated images to aid in clinical decision-making within their usual workflow.

The Aquilion Exceed LB is a whole-body multi-slice helical CT scanner that captures detailed cross-sectional images of the body, including the head. It incorporates AiCE, an AI-based noise reduction algorithm using deep convolutional neural networks, to improve image quality and reduce noise. This helps clinicians obtain clearer, more accurate diagnostic images for various body regions, including abdomen, pelvis, lung, cardiac, extremities, head, and inner ear.