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.
MVision AI Segmentation is a software device designed to automatically create segmentation templates of anatomical regions on CT images to assist clinicians in radiation therapy treatment planning. It uses machine learning-based algorithms to generate initial contours for multiple anatomical sites, which clinicians can review and modify before use, helping to save time and improve efficiency in clinical workflows.
The EFAI RTSuite CT HN-Segmentation System is AI-powered software designed to assist radiation oncology professionals by automatically contouring organs at risk in head and neck CT images. It helps streamline radiation therapy treatment planning by providing initial segmentations that clinicians review and edit, improving workflow efficiency and accuracy.
Contour ProtégéAI by MIM Software Inc. is an AI-powered software tool that helps trained medical professionals automatically create contours of anatomical structures on CT and MRI scans. The software uses machine-learning algorithms to segment normal organs and tissues, aiding in quantitative analysis and radiation therapy planning. It is intended to improve workflow efficiency and treatment accuracy by automating tedious contouring tasks.
VBrain is a software tool that helps medical professionals in planning radiation therapy for brain tumors. It uses artificial intelligence, specifically deep learning neural networks, to automatically outline brain tumors and organs at risk on MRI scans of the brain. This assists clinicians by providing initial contours that they can review and adjust, improving workflow efficiency and accuracy in treatment planning.
RT-Mind-AI is a software tool designed to automatically segment organs-at-risk in non-contrast CT images for patients undergoing radiation therapy. It helps radiation oncologists by providing accurate anatomical contours that support treatment planning and evaluation, improving workflow and precision.
Advanced Algorithms for Treatment Management Applications (AATMA) is a software library that uses machine-learning convolutional neural networks to automatically segment medical images. It provides derived data sets for use in radiation therapy treatment planning, accessible via an API and intended to help clinicians efficiently generate and review treatment contours from imaging data.
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.
Join hundreds of your peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.
We respect your privacy. Unsubscribe at any time.