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Reviewed 11 May 2026

Completeness Strong (72%)

CorEx

CorEx is artificial intelligence software for cardiac imaging. It prioritizes at-risk patients. It automatically analyzes coronary CT images (CCTA) images independently detecting and classifying coronary lesions quantitatively. CorEx automatically classifies stenosis according to the international CAD-RADS classification. CorEx aids the assessment of artery damage and the severity of the obstruction. It also provides an FFR AI prediction: for each coronary the solution predicts if the threshold of 80% is reached or not.

Supported by 5 papers

Key Features

Confidence score
FFR-AI prediction per coronary
Risk prioritization
Stenosis classification according to CAD-RADS

General Information

Product name

CorEx

Company

Spimed-AI

Modality

Main task

Not specified

Subspeciality

Cardiac

Disease targeted

Coronary stenosis

Regulatory Information

CE Certification

Pathway:

MDD

Class:

Class I

Verified by Health AI Register

Other certifications

Not specified

Evidence & Research

Peer-Reviewed Papers

Automated classification of coronary LEsions fRom coronary computed Tomography angiography scans with an updated deep learning model: ALERT study

European Radiology · Jan 2025

Artificial intelligence-enhanced detection of subclinical coronary artery disease in athletes: diagnostic performance and limitations

The International Journal of Cardiovascular Imaging · Oct 2024

Coronary artery disease detection using deep learning and ultrahigh-resolution photon-counting coronary CT angiography

Diagnostic and Interventional Imaging · Oct 2024

Coronary artery disease evaluation during transcatheter aortic valve replacement work-up using photon-counting CT and artificial intelligence

Diagnostic and Interventional Imaging · Feb 2024

Evaluation of a deep learning model on coronary CT angiography for automatic stenosis detection

Diagnostic and Interventional Imaging · Jan 2022

Technical Specifications

Patient population age

Not specified

Input

CCTA: MPR curvilinear images / 40° for the 3 main arteries (27 images)

Input format

DICOM

Output

Draft radiology report, worklist order, image annotations, risk score, table of quantified values, 3D visualization of coronary arteries with stenosis map

Output format

PDF

Integration

Stand-alone webbased

Deployment

Cloud-based, Locally on dedicated hardware, Locally virtualized (virtual machine, Docker)

Trigger for analysis

On demand, triggered by a user through e.g. a button click, image upload

Processing time

1 - 10 minutes

Population

Should not be used under the age of 12 years

Market Presence

On market since

03-2021

AI Platforms

Incepto

Resellers

Not specified

Countries present

Paying clinical customers

Not specified

Research/test users

Pricing Information

Pricing model

Subscription

Based on

Number of analyses, Number of ct scanners using application

Source: Vendor | First published: Jan 19, 2023 | Last updated: May 11, 2026