AI-Rad Companion Chest CT

Siemens Healthineers

The AI-Rad Companion Chest CT solution offers a multiorgan approach with pulmonary, cardiovascular and musculoskeletal functionalities. Major functionalities: lung lobe segmentation, lung lesion detection and measurements, pneumonia analysis, heart segmentation and calcium detection, aorta segmentation and diameter measurements, as well as vertebra body segmentation and measurement.
Product specifications Information source: Vendor
Last updated: Sept. 9, 2020
Product name AI-Rad Companion Chest CT
Company Siemens Healthineers
Subspeciality Chest
Modality CT
Disease targeted Lung cancer, pneumonia, osteoporosis, coronary artery disease
Key-features Segmentation and volume quantification of lungs, lung lobes, lung lesions, heart, thoracic aorta, coronary artery calcification, thoracic vertebrae; density quantification of lungs and vertebrae.
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps)
Data characteristics
Population All chest CT
Input Standardized CT Data, Slice thickness: ≤ 3mm, Axial Images and no gantry tilt, matrix size: 512 x 512, reconstruction kernel: Soft to medium, minimum of 3 slices
Input format DICOM
Output Image annotations, 3D Visualizations, Report with table of findings
Output format DICOM
Integration Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone webbased
Deployment Cloud-based
Trigger for analysis Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time 1 - 10 minutes
Certified, Class IIa
510(k) cleared, Class II
Market presence
On market since 05-2019
Distribution channels Teamplay Digital Health Platform
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model Subscription
Based on Number of analyses
Peer reviewed papers on performance
Non-peer reviewed papers on performance
Other relevant papers