Coreline Soft
Cononary Artery Calcium Scoring
Information source: Vendor
Last updated: April 22, 2022

General Information

Product name AVIEW CAC
Company Coreline Soft
Subspeciality Chest
Modality CT
Disease targeted Coronary Artery Disease
Key-features CAC score per branch, automatic segmentation, arterial age, Agatston, Volume, Mass score
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand), report suggestion

Technical Specifications

Data characteristics
Population All adult chest CT
Input Non enhanced, Cardiac gated CT
Input format DICOM
Output Score card with CAC score per branch, arterial age, Agatston, Volume, Mass score
Output format PDF, Secondary Capture, Encapsulated DICOM
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Stand-alone third party application, Stand-alone webbased, Server based
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based, Hybrid solution
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 , MDD
FDA 510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE) AVIEW CAC provides CAC analysis by segmentation of four main artery (right coronary artery, left main coronary, left anterior descending and left circumflex artery then extracts calcium on coronary artery to provide Agatston score, volume score and mass score by whole and each segmented artery type. Based on the score, provides CAC risk based on age and gender.


Market presence
On market since 11-2017
Distribution channels RMS Medical Devices, Alma AI MARKETPLACE, Eureka Clinical AI
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model Subscription, One-off payment
Based on Number of users, Number of installations


Peer reviewed papers on performance

  • Fully Automated Deep Learning Powered Calcium Scoring in Patients undergoing Myocardial Perfusion Imaging (read)

  • Deep Learning for Automatic Calcium Scoring in Population-Based Cardiovascular Screening (read)

Non-peer reviewed papers on performance
Other relevant papers