FDA Radiology AI Devices

The syngo.via RT Image Suite by Siemens is advanced software that helps clinicians visualize and manipulate 3D and 4D medical images from multiple modalities like CT, MRI, PET, and CBCT. It supports contouring tumors and organs at risk, image registration, and creating simple treatment plans, aiding radiation therapy preparation. The software includes AI-based deep learning for lung lobe segmentation to calculate lung ventilation, improving the accuracy and efficiency of radiation therapy planning.

MI View&GO is a software application developed by Siemens for medical professionals to review, manipulate, and analyze medical images from modalities like PET, SPECT, CT, and MRI. It integrates molecular imaging with anatomical data to support disease management in oncology, cardiology, neurology, and organ function, and aids in radiotherapy planning. The software enhances image processing efficiency directly at the scanner console, allowing for timely quality assessment and basic reading of images.

The SKOUT Software is an artificial intelligence (AI) based computer-aided detection tool designed to assist gastroenterologists during colonoscopies by identifying potential colorectal polyps in real time. It processes high-definition endoscopic video and highlights suspected polyps with visual markers on the video feed, helping clinicians detect polyps more effectively and support colorectal cancer screening and surveillance.

DeepRhythmAI is a cloud-based AI software that automatically analyzes two-lead ECG data to detect cardiac arrhythmias. It supports healthcare professionals by providing analysis results that need to be reviewed and confirmed. It is designed for integration into other medical devices or software platforms and assists clinicians in identifying rhythm issues in adult patients.

The ZEUS System (Zio Watch) is a prescription-based wearable device and software system that uses AI to analyze cardiac signals from an ECG and PPG sensor to detect and report atrial fibrillation. It provides clinicians with detailed reports to aid in diagnosing and managing atrial fibrillation in adult patients.

The Study Watch with Irregular Pulse Monitor by Verily Life Sciences is a wearable device designed for adults diagnosed with or at risk for atrial fibrillation (AF). It continuously monitors heart rhythms using photoplethysmography (PPG) and single-channel ECG measurements. The device notifies users of irregular pulses, prompting ECG collection, and securely transmits data for healthcare provider review. This aids early detection and monitoring of AF, enabling timely clinical intervention.

The Eko Murmur Analysis Software (EMAS) is a cloud-based AI-driven tool that analyzes heart sound and ECG data to detect and classify heart murmurs, distinguishing between innocent and structural murmurs. It supports clinicians by offering decision support in evaluating heart sounds, enhancing the diagnostic process for pediatric and adult patients without replacing clinical judgment.

IDx-DR v2.3 is an AI-based diagnostic software that automatically detects more than mild diabetic retinopathy from retinal images captured with a Topcon NW400 fundus camera. It helps healthcare providers identify patients who need referral to eye care professionals, improving timely diagnosis and management of diabetic retinopathy.

ART-Plan is an advanced software tool designed to assist medical professionals in cancer radiotherapy planning. It supports visualization and manipulation of 3D multi-modal medical images (CT, MR, PET-CT, CBCT, 4D-CT) and includes AI-driven automatic and semi-automatic segmentation of organs at risk and lymph nodes. It also allows image registration and generation of synthetic CT images from MRI, facilitating precise and efficient radiation treatment planning.

The Atrial Fibrillation History Feature is a software application designed to analyze pulse rate data from Apple Watch sensors to detect episodes of irregular heart rhythm indicative of atrial fibrillation (AFib). It provides users with estimates of the amount of time spent in AFib over past periods and visualizes this alongside lifestyle data to help users understand the impact of their behavior on their condition. It assists patients in monitoring AFib burden over time but is not meant to replace traditional diagnosis or treatment methods.