Rayscape's Lung CT solution helps radiologists identify lung nodules that have a diameter between 3-30 mm. The algorithms highlight the presence of nodules on each slice and, separately, measures the diameter and volume of the identified ones. Rayscape CT is also able to compare lung nodules characteristics between different investigations and to generate a report with their evolution.
Rayscape Lung CT identifies lesions caused by SARS-CoV2 infection and quantify them volumetrically.

*The company was previously named XVision, and the product CTXVISION
Product specifications Information source: Vendor
Last updated: May 25, 2023
Product name Lung CT
Company Rayscape
Subspeciality Chest
Modality CT
Disease targeted Lung cancer, COVID19
Key-features Nodules detection, nodules localization, nodules measurements, volume calculation, diameter calculation, malignancy score, automatic comparison of nodules, SARS-Cov2, SARS-CoV2 lesion quantification
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps)
After: diagnosis verification
Data characteristics
Population Rayscape Lung CT can be used for adults, clinical population and screening population.
Input 3D, contrast, non-contrast, multi-slice, single-slice, slice thickness <3mm
Input format DICOM
Output Nodules detection and localization overlay, table of calculated measurements, table with nodules evolution
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration via AI marketplace or distribution platform
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based
Trigger for analysis Automatically, right after the image acquisition
Processing time 1 - 10 minutes
Certified, Class I , MDD
No or not yet
Market presence
On market since 05-2021
Distribution channels Infinitt
Countries present (clinical, non-research use) 5
Paying clinical customers (institutes) 100
Research/test users (institutes) 6
Pricing model Pay-per-use, Subscription
Based on Number of analyses
Peer reviewed papers on performance

  • Evidence of a cognitive bias in the quantification of COVID-19 with CT: an artificial intelligence randomised clinical trial (read)

Non-peer reviewed papers on performance

  • Artificial Intelligence in Computed Tomography - Lung Nodule Analysis Algorithm (read)

Other relevant papers

  • Medical Whitepaper Rayscape (read)