contextflow SEARCH Lung CT is a 3D image-based search engine (currently it looks for 19 disease patterns in lung CTs). It identifies and matches relevant, visually-similar disease patterns to aid in diagnosis. By marking a region of interest in the image, contextflow SEARCH returns reference cases and associated knowledge and medical literature relevant for differential diagnosis. It integrates directly into the following PACS: Agfa, Medigration, Philips, Sectra.
Product specifications Information source: Vendor
Last updated: Sept. 15, 2021
General
Product name contextflow SEARCH Lung CT
Company contextflow
Subspeciality Chest
Modality CT
Disease targeted Airway wall thickening, atelectasis, bronchiectasis, bulla, consolidation, cyst, effusion, emphysema, ground-glass opacity, honeycoming, mass, mosaic attenuation pattern, nodular pattern, nodule, pneumothorax, pulmonary cavity, reticular pattern, tree-in-bud
Key-features Content-based image retrieval, pattern classification, lung anomaly detection
Suggested use During: interactive decision support (shows abnormalities/results only on demand)
Data characteristics
Population CT scans in which lung-specific image patterns should be identified and interpreted
Input 3D chest CT scans of the lungs
Input format DICOM
Output Visually-similar and expert-labeled images, lung anomaly overlays, classification of selected image regions
Output format Interactive user-interface, web-application
Technology
Integration Integration in standard reading environment (PACS)
Deployment Locally virtualized (virtual machine, docker), Hybrid solution
Trigger for analysis Automatically, right after the image acquisition
Processing time > 10 minutes
Certification
CE
Certified, Class IIa , MDR
FDA
No or not yet
Market presence
On market since 10-2019
Distribution channels Sectra Amplifier Store, Wellbeing Software
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes) 10+
Pricing
Pricing model Pay-per-use, Subscription
Based on Number of analyses
Evidence
Peer reviewed papers on performance Forthcoming 2021
Non-peer reviewed papers on performance
Other relevant papers