KardiolabsAI provides AI-driven software that automatically analyzes CT coronary angiogram images to detect blockages, quantify stenosis, and calculate calcium scores, delivering faster, cost‑effective cardiac diagnoses. Their deep‑learning platform integrates a generative AI assistant to explain results, helping cardiologists and radiologists make quicker, more consistent treatment decisions, especially in settings with limited specialist access.
Funding
Funding not disclosed
Founders
Product
Problem
Cardiologists and radiologists must manually interpret CT coronary angiograms to identify blockages, calculate calcium scores, and assess functional significance, a process that is time‑consuming, costly, and subject to inter‑observer variability. Limited access to expert readers in remote or underserved regions further delays diagnosis and treatment decisions for coronary artery disease.
Solution
KardiolabsAI offers an AI‑driven software platform that automatically analyzes both static and cine CT coronary angiogram images to detect and quantify coronary stenoses, compute calcium scores, and generate virtual fractional flow reserve (FFR) assessments. The system produces structured diagnostic reports and integrates a generative‑AI assistant that explains findings in plain language for clinicians and patients. By delivering rapid, reproducible results without manual segmentation, the platform reduces interpretation time, lowers costs, and supports more consistent decision‑making across care settings.
Target Audience
Primary users are cardiology and radiology departments in hospitals and imaging centers that perform CT coronary angiography, as well as tele‑cardiology services seeking automated interpretation tools.
Features
- Deep‑learning models that segment coronary arteries and identify stenosis severity across the full CT dataset
- Automated calcium scoring for both chest and cardiac CT scans with validated Agatston metrics
- Virtual FFR calculation using AI‑derived hemodynamic modeling to estimate functional impact of lesions
- End‑to‑end workflow that generates a comprehensive report, including quantitative metrics and visual overlays
- Integrated generative AI chatbot that provides natural‑language explanations of diagnostic results and prognosis
- Cloud‑based processing pipeline ensuring scalability and secure handling of patient imaging data