Find the artificial intelligence based software for radiotherapy that you are looking for. All products listed are available for the European market (CE marked).
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Workflow phase:
Modality: CBCT
Source:
No key features available
No description available
Workflow phase: Contouring
Modality: Contrast-enhanced CT, CT
Source: Public
Autosegmentation of OAR
aview:RT ACS conducts automatic segmentation of normal organs using deep learning AI technology
Workflow phase: Contouring
Modality: CT, MR
Source: Public
Autosegmentation
Contour ProtégéAI+ is an accessory to MIM software that automatically creates contours on medical images through the use of machine-learning algorithms. It is designed for use in the processing of medical images and operates on Windows, Mac, and Linux computer systems. Contour ProtégéAI+ is deployed on a remote server using the MIMcloud service for data management and transfer; or locally on the workstation or server running MIM software.
Workflow phase: Contouring
Modality: CT, MR, PET/CT, sCT
Source: Public
CE
FDA
Autosegmentation
AccuContour offers AI auto-contouring for OARs, lymph nodes, tumor targets, and supports user self-trained models.
Workflow phase: Contouring
Modality: CT, MR
Source: Public
AI-based revisions, Autosegmentation
Active Contouring technology for dynamic segmentation: Mediq RT features proprietary Active Contouring, enabling clinicians to manually adjust any segment in real time. The AI algorithm automatically propagates the correction across the remaining slices or relevant volumes, allowing for interactive fine-tuning without interrupting the overall segmentation process.
Workflow phase: Contouring
Modality: CT
Source: Public
Autosegmentation
ProSoma® Dart is the new module in the ProSoma® family of toolkits which enables the fully automatic anatomical contouring using a state of the art Segmentation algorithm.
Workflow phase: Contouring
Modality: CT, MR
Source: Public
Autosegmentation of brain metastases, Autosegmentation of lymph nodes, Autosegmentation of OAR
AI Contouring for Eclipse automatically generates contours from CT and MRI images for over 200 anatomical structures, including organs-at-risk, lymph nodes, and brain metastases.
Workflow phase: Contouring, Imaging
Modality: CBCT, CT, MR, PET/CT
Source: Vendor
Autosegmentation, Image Registration, Synthetic CT Generation, Workflow Automation
AutoContour is a software solution designed to assist with the delineation of anatomical structures for radiotherapy treatment planning. It uses deep learning models, including convolutional neural networks, to automatically generate contours from CT, MR, and CBCT imaging data. The system supports integration with treatment planning workflows via DICOM and ESAPI scripting for Eclipse and provides tools for reviewing and editing generated structures to support clinical use.
Workflow phase: Contouring, Imaging, Plan evaluation, Planning
Modality: CBCT, CT, MR, PET/CT
Source: Vendor
CE
FDA
Autosegmentation, Image Enhancement, Image Registration, Plan Generation/Optimisation, Synthetic CT Generation, Workflow Automation
ART-Plan is an AI-based software platform developed by TheraPanacea to support radiotherapy treatment planning workflows. The platform provides authorized users with a set of software modules designed to assist in the preparation, assessment, and management of radiotherapy treatment planning activities using medical imaging data. ART-Plan operates through a user account system that provides access to functions based on predefined user rights and permissions. The system supports both Cloud and On-premise deployments. The software includes tools for image and plan import, organization, analysis, and processing of medical imaging data used during the radiotherapy planning process. Depending on the modules installed and licensed, ART-Plan supports activities such as contouring organs at risk or tumors, automated protocol-based treatment plan generation based on predicted class solution, and adaptive treatment assessment based on AI-generated synthetic-CT. The tasks are automated, can be performed simultaneously on multiple patients, and the results are exported to the Treatment Planning System for further review, editing and approval.
Workflow phase: Contouring
Modality: CT, MR
Source: Public
Autosegmentation of OAR
Deep-learning based autocontouring with machine learning-trained algorithms for CT.
Workflow phase:
Modality:
Source: Public
Autosegmentation of OAR
DirectORGANS (Optimized Reconstruction based Generative Adversarial Networks) employs an optimized reconstruction that is used as a standardized input to the Deep Learning based autocontouring algorithm. Both processes, image optimization and automatic contouring, are embedded into the CT simulator enabling results as part of the image acquisition.
Workflow phase: Contouring
Modality: CT, MR
Source: Public
Autosegmentation of OAR
AI-Rad Companion Organs RT automatically contours several organs at risk. This input can be used for further processing in a treatment planning system. This enables physicians to free up resources for other time-consuming tasks and drives standardization across different individuals and institutions.