FDA Radiology AI Devices

Ceevra Reveal 3 is a software medical device designed for processing, reviewing, and analyzing 3D images created from CT and MR scans. It helps clinicians with preoperative surgical planning and intraoperative image display, including interacting with 3D visualizations using mobile or desktop viewers, and even VR headsets. By using AI-driven algorithms, it generates preliminary segmentations of normal anatomical structures to assist healthcare professionals in their clinical decisions for adult patients.

ART-Plan is a medical imaging software that helps clinicians visualize, contour, and process 3D multi-modal images like CT, MR, and PET-CT for cancer patients undergoing radiotherapy. The software uses AI to automatically delineate organs at risk and lymph nodes to assist in treatment planning, saving time and improving precision. It also supports image registration and generation of synthetic CT images from MRI.

Brainlab Elements Trajectory Planning (2.6) is a software designed to help neurosurgeons plan the best paths for surgical instruments during cranial procedures, such as electrode placements or biopsies. It uses anatomical images from scans to plan and guide minimally invasive or open surgeries, enhancing precision and improving patient outcomes.

The SKOUT system is an AI-powered software tool that helps gastroenterologists detect potential colorectal polyps in real time during colonoscopy procedures. By providing visual markers on the colonoscopy video feed, it aids trained specialists in identifying polyps that might be missed, supporting better colorectal cancer screening and surveillance.

RayStation 12A by RaySearch Laboratories is a comprehensive radiation therapy treatment planning system that allows users to import patient images, define treatment targets, optimize and evaluate radiation treatment plans, and administer them. It supports multiple imaging modalities including CT, PET, and MR, enhancing precision in oncologic care by helping clinicians design effective and tailored radiation treatments while ensuring safety and accuracy.

NeuroRPM is a software application for the Apple Watch that uses machine learning to analyze motion sensor data to quantify motor symptoms like tremor, bradykinesia, and dyskinesia in adult Parkinson's disease patients. It helps clinicians remotely monitor symptom presence every 15 minutes, supporting both clinic and home use for improved patient management.

The Xeleris V Processing and Review System by GE Healthcare is a software platform designed for processing, reviewing, and analyzing nuclear medicine and PET imaging data. It supports various clinical applications including brain, lung, cardiac, liver, and bone imaging analyses, aiding physicians in diagnosis and treatment planning by providing enhanced image visualization, quantification, and monitoring of patient radiation doses.

The Belun Sleep System BLS-100 is a wearable device designed for adult patients suspected of sleep apnea. It consists of a sensor ring worn on the user's index finger overnight to collect biophysical signals such as oxygen saturation and pulse, which are then analyzed by AI-powered software to help healthcare professionals assess the severity of sleep-related breathing disorders in both clinical and home settings.

The ZEUS System by iRhythm Technologies is a software platform designed to analyze ECG data from wearable cardiac monitors to detect arrhythmias and other heart rhythm abnormalities. It uses AI algorithms to automatically process and identify cardiac events, assisting clinicians in diagnosing and managing heart conditions by generating detailed reports from long-term ECG recordings.

Oncospace is a software tool that assists radiation oncologists and medical dosimetrists in planning radiotherapy treatments for patients with cancer in the prostate, head, and neck regions. It uses locked machine learning algorithms to predict achievable dose objectives for organs at risk based on the patient's anatomy and automates aspects of treatment plan optimization. This helps clinicians customize treatment protocols, optimize radiation dose delivery while sparing healthy tissue, and review treatment plans efficiently, ultimately supporting better patient care in radiation oncology.