Goethe‑CVI™ Approaches is an AI‑driven platform that automates the full cardiac MRI workflow, from standardized scan acquisition to automatic image recognition, quantitative analysis, and structured report generation. By providing real‑time feedback during scanning and evidence‑based risk scoring, it reduces operator effort, speeds diagnosis, and supports consistent, data‑rich reporting for hospitals and cardiac imaging centers.
Funding
Funding not disclosed
Founders
Product
Problem
Cardiac magnetic resonance imaging (CMR) workflows are labor‑intensive, requiring specialized operators for image acquisition, manual post‑processing, and expert interpretation, which limits throughput and increases costs in clinical practice.
Solution
Goethe‑CVI™ Approaches delivers a fully integrated, AI‑driven platform that automates the entire CMR pathway—from standardized scan protocol execution to automatic image recognition, quantitative analysis, and structured report generation. Real‑time feedback during acquisition reduces user interaction and streamlines the scanning process, while cloud‑based post‑processing applies evidence‑based cut‑offs and risk scores to produce machine‑readable outputs. The system generates report suggestions and therapy recommendations, enabling clinicians to make faster, more consistent diagnoses without extensive manual effort. Seamless integration with existing hospital information systems via HL7 and structured DICOM ensures the solution fits into current workflows.
Target Audience
Primary customers are hospitals, cardiac imaging centers, and cardiology/radiology departments that perform cardiac MRI and seek to increase efficiency and diagnostic consistency.
Features
- AI‑powered acquisition modules that guide operators and reduce scan time by up to 65%
- Automatic image recognition and quantitative post‑processing of all CMR sequences
- Evidence‑based classification using built‑in cut‑off values and risk score calculators
- Real‑time generation of structured reports with therapy suggestions and AI‑derived risk assessments
- Cloud architecture with HL7 and DICOM integration for seamless workflow incorporation
- Curated database linking imaging, proteomics, and outcome data to support research and personalized medicine