The AI4CMR software performs a automatic cardiac segmentation and interpretation of Cardiac Magnetic Resonance (CMR), allowing quantification of various parameters without the need for intervention by a medical professional.
It automatically identifies cases with normal left ventricle wall motion (regional contractility), aimed at increasing awareness for the cases with suspicious wall motion abnormalities to the reporting physicians.
Product specifications Information source: Vendor
Last updated: Sept. 21, 2021
Product name AI4CMR
Company AI4MedImaging
Subspeciality Cardiac
Modality MR
Disease targeted Cardiac failure, Ischemic heart disease, Valvular heart disease, Cardiomyopathy, Cardiac function and morphology, Hypertensive cardiac disease, other pathologies that need assessment of cardiac function and morphology
Key-features Heart ventricles segmentation, quantification of ventricular volumes, myocardial mass, and ejection fraction, wall motion classification
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand), report suggestion
Data characteristics
Population Patients examined by CMR imaging. Not recommended for children (age < 18yo).
Input 3D, 4D, Cine MRI, short-axis (mandatory), 2-chamber (optional), 3-chamber (optional), 4-chamber (optional), patient sex (mandatory), patient age (mandatory), patient height (optional), patient weight (optional), patient heart rate (optional)
Input format DICOM
Output Heart ventricles segmentation coordinates, report with values of ventricular volumes, myocardial mass, and ejection fraction, binary assessment of wall motion normality
Output format JSON
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration CIS (Clinical Information System), Integration via AI marketplace or distribution platform, Stand-alone third party application, Stand-alone webbased
Deployment 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 10 - 60 seconds
Certified, Class IIa , MDR
No or not yet
Market presence
On market since 09-2021
Distribution channels
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model Pay-per-use, Subscription, One-off license fee
Based on Number of analyses
Peer reviewed papers on performance
Non-peer reviewed papers on performance
Other relevant papers