Cardiovascular Imaging AI
Ground-Truth Labels That Power Real-World, Regulatory-Ready Cardiovascular AI. We deliver finely segmented, expert-verified annotations designed to train AI in the complex realities of cardiac and vascular care.
Core Capabilities
Advanced technology built for enterprise scale.
Cardiac Imaging Annotation
Detailed annotations for CT (CCTA) coronary arteries, Cardiac MRI segmentation of ventricles and myocardium, and Ultrasound (Echocardiography) for valve leaflets and chamber boundaries.
Vascular Imaging Annotation
Segmentation of Intracranial arteries (Circle of Willis), Carotid Arteries, full-length Aorta, Peripheral Arteries, and Limb Veins for stroke and DVT risk analysis.
Interventional Cardiology Support
Data annotation for AI-powered imaging and procedural guidance systems supervised by board-certified interventional cardiologists and cardiac surgeons.
Coronary Angiograms & Procedural Videos
Vessel segmentation, lesion annotations, anatomical landmarks, and device segmentation with step-wise labeling for procedural context.
Echocardiograms & EHR Notes
Chamber segmentation, functional metrics, diagnosis coding, NLP-based findings, outcome labels, and temporal clinical markers.
Audit-Ready, Compliant Workflows
Our framework tracks every dataset with transparency, combined with CFR Part 11–aligned processes for smoother regulatory clearances.
Proven Applications
See how industry leaders are leveraging our solutions in production environments.
Discuss Your Use Case
AI for Interventional Cardiology
Expert-labeled angiograms, echocardiograms, procedural videos, and EHRs power AI systems for automated angiogram interpretation, real-time catheter guidance, plaque detection, and outcome prediction.
Coronary and Valvular Assessment
Train AI to compute calcium scores, identify leaflet thickening, and assess stenosis from expertly labeled CCTA scans.
Cardiac MRI Functional Analysis
Gold standard contours of ventricles, atria, myocardium, pericardial fat, and late-gadolinium scars enable AI models to quantify cardiac function and assess metabolic risk.
Echo-Guided AI for EF and CHD Screening
Annotated echo clips support AI calculation of ejection fraction, wall motion, and early detection of congenital defects.
Stroke Prevention
Detailed vascular annotations help models predict cerebrovascular events based on plaque burden and vascular anomalies.
Aortic Disease Management
Precise segmentation of aneurysms, dissections, and grafts enables AI to track anatomical changes after TAVR, EVAR, or TEVAR procedures.
Data Annotation for Intelligent Interventional Cardiology Systems
Coral Mountain Data supports the development of AI-powered imaging and procedural guidance systems in interventional cardiology through precise data annotation, supervised by board-certified interventional cardiologists, cardiac surgeons, electrophysiologists, and cardiac imaging specialists. This enables automated angiogram interpretation, real-time catheter and stent guidance, high-risk plaque detection, ejection fraction and valve assessment, procedure phase recognition, outcome prediction and risk scoring, and automated report generation.
Coronary Angiograms
Vessel segmentation, lesion annotations, quantitative metrics, anatomical landmarks, procedural context.
Echocardiograms
Chamber segmentation, view classification, functional metrics, disease grading.
Procedural Videos
Device segmentation, step-wise labeling, event timing, outcome tagging.
EHR Notes
Diagnosis coding, NLP-based findings, outcome labels, temporal markers and clinical scores.
Why This Matters Now
The cardiovascular imaging field is rapidly evolving. Noninvasive modalities are becoming the frontline tools—not just for screening, but for interventional planning and outcome tracking. Meanwhile, AI models are expected to deliver accuracy, explainability, and regulatory transparency—all at scale. Whether you're building tools for structural heart procedures, aortic disease monitoring, or risk prediction in heart failure, your model is only as good as the data it learns from.