FDA Radiology AI Devices

TAIMedImg DeepMets is a software tool that uses artificial intelligence to assist medical professionals by automatically outlining brain metastases on MRI scans. This helps speed up the workflow for planning radiation therapy treatment in patients with diagnosed brain metastases, ensuring accurate contours that clinicians can verify and adjust as needed.

AI-Rad Companion Organs RT is an AI-powered software that automatically segments predefined organs-at-risk from CT and MR images. It helps radiation oncologists by generating contours used in treatment planning, streamlining workflow and improving efficiency. The contours produced are reviewed and edited by trained professionals before use in radiation therapy.

OncoStudio (OS-01) is a software tool that uses deep learning to automatically outline organs at risk in CT scans. This helps clinicians and radiation oncologists efficiently generate contouring for treatment planning by providing initial contours that can be reviewed and confirmed. The software supports multiple anatomic regions including head & neck, thorax, abdomen, and pelvis, and outputs results in DICOM-RT format compatible with radiation therapy systems.

Contour ProtégéAI+ is a medical imaging software accessory that leverages machine-learning algorithms to automatically create contours of anatomical structures on CT and MR images. It supports clinicians by automating and assisting in image segmentation, which is critical for adaptive therapy, radiation treatment planning, and patient follow-up. The software provides significant time savings and improves contouring consistency, while allowing clinicians to review and edit results as needed.

AutoContour (Model RADAC V4) by Radformation, Inc. is a software tool designed to automatically contour anatomical structures on CT and MR images to aid radiation treatment planning. Using machine learning, it helps clinicians create accurate contours of organs and tissues, streamlining the preparation process for radiation therapy and improving planning precision.

Contour+ (MVision AI Segmentation) is a software tool that uses machine learning algorithms to automatically create contour outlines of anatomical regions on CT and MRI scans. It assists clinicians in radiation therapy planning by providing initial segmentations of organs and tissues, which professionals can review and modify before treatment planning. This speeds up the workflow and improves efficiency in radiation treatment preparation.

Limbus Contour is a software tool designed to help medical professionals automatically create accurate contours of healthy anatomical structures from CT and MRI images. These contours are used to plan and evaluate radiation treatment for cancer patients, improving efficiency and consistency in treatment preparation.

DeepContour (V1.0) is a software tool that uses deep learning to automatically segment organs on CT images for radiation therapy planning. It helps trained healthcare professionals by generating and editing organ contours, performing 3D reconstruction, and analyzing anatomical structures. By automating these tasks, it improves workflow efficiency and supports precise radiation treatment planning.

AI-Rad Companion Organs RT is an AI-powered medical imaging software designed to automatically segment organs from CT and MR scans to assist radiation therapy treatment planning. It uses deep learning algorithms to produce contours of organs-at-risk, which clinicians can review and edit before using them in treatment planning systems. This software saves time and improves the accuracy of radiation therapy preparation by providing automated organ delineation, intended for use by trained medical professionals.

QOCA® image Smart RT Contouring System is an AI-powered post-processing software designed to automatically outline organs at risk on CT scans. This helps radiation oncology clinicians efficiently prepare treatment plans by providing accurate organ contours as input data for radiation therapy, improving workflow and precision in treatment delivery.