FDA Radiology AI Devices

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.

VBrain-OAR is a software device from Vysioneer Inc. designed to assist trained radiotherapy personnel in brain tumor radiation therapy treatment planning by automatically generating contours of organs at risk in brain MRI images using AI deep learning. It also provides image registration functions to align multi-modality medical images. This device supports clinicians by providing initial contour outlines to improve the efficiency and consistency of radiation treatment planning, while still requiring final confirmation by qualified personnel.

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.

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.

VBrain is an AI-powered software device that helps trained medical professionals by automatically generating initial contours of known brain tumors on MRI scans. It supports radiation therapy planning by providing preliminary tumor outlines for professionals to review and adjust, streamlining the clinical workflow for brain tumor treatment planning.

ART-Plan is a medical software tool that helps clinicians plan radiation therapy for cancer patients. It supports image registration and fusion of CT, PET, and MRI scans to better visualize tumor and healthy tissues. It offers automatic, semi-automatic, and manual contouring of organs at risk and lymph nodes, saving time and improving precision in treatment planning. The software is meant for use by trained professionals in clinical settings.

AI-Rad Companion Organs RT by Siemens is a post-processing AI software that automatically contours organs at risk on CT images to aid radiation therapy treatment planning. It uses deep learning algorithms to generate organ contours that can be reviewed and accepted by trained medical professionals, helping streamline radiotherapy preparation and ensure accurate targeting of treatment.

AutoContour is a software tool that helps radiation treatment planners automatically contour and review anatomical structures in medical images, primarily CT scans, to prepare for radiation therapy treatment planning. It uses cloud-based machine learning algorithms to produce initial contours, and provides a web interface for review and editing, enhancing efficiency and accuracy for clinicians.

Contour ProtégéAI is a software tool designed to assist medical professionals by automatically creating anatomical contours on CT and MR medical images using machine learning. It supports applications such as adaptive therapy, radiation treatment planning, and management of patient images. The software requires manual review and editing of contours to ensure accuracy, improving clinical workflow efficiency and patient care.

AccuContour is a standalone software designed for radiation oncology departments. It uses AI-based deep learning to automatically contour organs at risk on non-contrast CT images and to register multimodality medical images. This helps clinicians in treatment planning, evaluation, and adaptation, improving workflow efficiency and accuracy in radiation therapy.