AI powered by RUBEE™
Forward-thinking and clinically relevant
‘Augmented Intelligence’ does just that: offering a set of tools that let your clinicians maximize the value of their own expertise, increase their productivity and enhance the diagnostic process. But to get the real benefits to your clinicians, the tools need to be embedded right into the workflows and systems they use every day.
RUBEE™ for AI, as part of your Enterprise Imaging platform, offers a seamless AI experience for your clinicians.
Carefully curated ‘packages’ embed best-of-class AI apps that work seamlessly to support your real clinical workflow from start to finish. With RUBEE for AI, you get more out of your AI investments, while enriching the value of your Enterprise Imaging. It’s a win-win-win for your hospital, your clinicians and your patients!
INNOVATION – RUBEE™ for AI
With RUBEE™ for AI, you can embed our AI specialty packages into your clinical workflows.
RUBEE visualizes the metadata generated by algorithms and uses that information to automate and optimize your workflows, all within your Enterprise Imaging ecosystem.
- Task assignments and case distribution are smoothly automated.
- Hanging protocols get ‘smart’, with dedicated reading protocols.
- Report automation by auto-including AI results into the reporting workflow.
RUBEE™ for AI helps your clinicians to focus their efforts on cases that require immediate attention.
“Reduce 3D reading time to about 35 seconds.”
Combining the Breast AI package with the workflow features of RUBEE™ for AI, offers radiologists advanced visualizations and workflow optimization.
The Breast AI package sorts and rates images intelligently using a deep learning algorithm. With automated task prioritization, smart display of findings and dedicated reading protocols, it speeds up reading, optimizes workflow and improves early detection.
Evidence based benefits:
- Improves both 2D and 3D breast cancer detection accuracy
- Catches cancers earlier
- Enhances Radiologist performance
- Reduces both reading times and workload
The workflow is automated, the radiologist’s workload is significantly eased, and patients are more quickly started on their diagnostic pathway.
*FDA cleared and CE marked for both 2D and 3D mammography
“29% reduction in missed nodules.”
The CT Lung AI package enables advanced visualization and workflow automation and optimization, dedicated to the CT Lung specialty.
It increases the accuracy of reading lung CTs, while reducing overall reading time, for greater productivity.
Reliable and consistent results support confident, faster diagnoses, to get the patient onto a treatment pathway more quickly. Automated comparison of prior and current images will help identify new lesions and measure changes, for secure follow-up
- Processing of scans from a wide range of manufacturers and acquisition protocols
- Unprecedented detection, segmentation and characterization accuracy of lung nodules
- Support for non-contrast and contrast chest CT
- Reduced burden of visual search and assessment by suppressing vascular structure
*ClearRead CT is the first FDA-cleared system for concurrent reading, for all nodule types
“17% Improved Nodule detection”
“19 % Faster Reads”
A leap forward for reading efficiency and fast results
RUBEE for AI brings carefully curated augmented intelligence packages for your Enterprise Imaging clinical workflows. The Agfa HealthCare Chest-X-Ray AI Visualisation Package is powered by the Riverain Technologies™ ClearRead™ Xray platform.
It is comprised of three FDA-cleared applications designed to improve reading efficiency and accuracy across the hospital enterprise without requiring additional dedicated hardware. The solution optimizes the diagnostic value of all portable and upright images.
- Enterprise-wide capability powered by acquisition normalization technology that allows “plug in” ability across all manufacturers and diverse imaging protocols.
- High throughput, scalable computation on off-the-shelf hardware and virtual machine deployments.
- No additional radiation dose or changes to existing imaging protocols are required.
- Reduces the time spent for visual search and assessment.
- Automatically inserts the images into the patient’s le for instant access.
“97-99% AUROC – Very high-performance level”
“34% reduced reading time”
Introducing the Chest X-Ray AI Analysis package Powered by RUBEE™ and INSIGHT CXR
- Agfa’s RUBEE for AI enables EI Desktop and XERO Universal Viewer AI visualizations
- INSIGHT CXR is CE cleared
- INSIGHT CXR helps detect 10 common chest x-ray findings and generates the analysis result which indicates the presence and the location of chest abnormalities.
- Detection of areas of suspicious abnormal radiologic findings
- Automated analysis of chest radiographs via deep learning technology
- Visualization and quantitative estimation of the likelihood of the presence of each abnormality
Chest X-ray AI Analysis Package – Major features
- Fast triage of normal cases
- Efficient reading via exam prioritization
- Improved reading performance
- Reduced overlooked lung cancers
- Streamlined ED workflow
- COVID 19 patient triaging and monitoring
Product may not be available in all regions, contact your Agfa HealthCare representative for details
“Self-learning algorithms offer tremendous opportunities in many domains. In radiology, AI will definitely change how services are delivered. Agfa HealthCare is investing in these new AI technologies. We will integrate them into the Enterprise Imaging platform, and thus into our own workflows. “
Prof. Dr. Eric Achten Ghent University Hospital Belgium
Distinguishing Hype from Reality – A Frost & Sullivan White Paper
A Practical Guide for the Implementation of Artificial Intelligence in Medical Imaging
Approximately 75% of all clinical decisions are based on medical imaging, and a large quantum of this imaging data is stored in a digital format. But for a long time, this digital data was left unutilized because of the lack of appropriate technologies to extract useful insights from this data.
The potential of Artificial Intelligence to improve efficiency, reduce operating costs and improve quality of care indicates it will transform the medical imaging industry significantly.
