FDA Radiology AI Devices

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.

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.

Contour ProtégéAI by MIM Software Inc. is a medical imaging software that assists trained medical professionals by automatically creating contours on CT and MR images using machine learning. It helps in radiation therapy by segmenting anatomical structures and specific tissues like the prostate and urethra from imaging data, improving efficiency and accuracy in treatment planning. The software works on multiple platforms and supports cloud or local deployment, allowing users to review and edit automated results for patient management and follow-up.

EFAI RTSUITE CT HCAP-Segmentation System is an AI-powered software tool designed to assist radiation oncology professionals by automatically outlining critical organs at risk on CT scans. It helps radiation therapists plan treatments more efficiently by providing initial organ contours that clinicians can review and adjust, improving workflow while ensuring safety and accuracy.

Auto Segmentation by GE Medical Systems is an AI software tool that automatically generates organ-at-risk contours from CT scans to help radiation oncologists, medical physicists, and dosimetrists speed up radiation therapy planning. It produces initial segmentation contours that users can review and adjust, improving workflow efficiency and precision in radiation treatment.

AutoContour Model RADAC V3 is an AI-enabled software designed to automatically contour anatomical structures in CT and MR images to assist radiation treatment planners in preparing radiation therapy plans more efficiently. It uses deep learning models to generate contours of organs and tumors, allowing clinicians to review and adjust as needed, which streamlines the treatment planning process and improves accuracy.

Contour ProtégéAI is a medical imaging software accessory designed to assist trained medical professionals by automatically creating anatomical contours on CT and MR images using machine learning. It helps in radiation therapy planning by segmenting various body structures, including the prostate and pelvic organs, enabling quantitative analysis, adaptive therapy, and patient follow-up. Results generated by the AI can be reviewed and edited to ensure accuracy.

AccuContour is a software for radiation oncology departments that uses AI-based deep learning to automatically register multi-modality medical images and segment non-contrast CT images. It assists clinicians in treatment planning, evaluation, and adaptation by generating critical imaging information, thus improving workflow efficiency and patient care in radiation therapy.

AVIEW RT ACS is a software solution developed by Coreline Soft Co., Ltd. that uses deep learning AI to automatically segment organs and generate contours from CT scans. It is intended to assist clinicians, particularly in radiation oncology, by providing initial organ contours for treatment planning, saving time and improving accuracy.

AI-Rad Companion Organs RT is a software product by Siemens that uses deep learning to automatically contour organs at risk on CT imaging data. The output contours help radiation oncologists plan external beam radiation therapy by providing accurate anatomical structures for treatment planning. The software processes CT scans, generates contour data in DICOM RTSTRUCT format, and integrates with treatment planning systems to improve clinician workflow and efficiency in radiation therapy preparation.