Vista AI Scan uses AI algorithms to automate cardiac MRI acquisition, providing real‑time protocol selection, slice positioning, breath‑hold guidance, and automatic parameter optimization. The platform shortens exam time, standardizes image quality, and integrates with existing MRI consoles and PACS, allowing hospitals and imaging centers to increase throughput without additional hardware.
Funding
Funding not disclosed
Founders
Product
Problem
Cardiac MRI programs face increasing patient demand, staffing shortages, and complex scan protocols that lead to long exam times, inconsistent image quality, and limited throughput. These constraints reduce patient access to high‑quality diagnostic imaging and increase technologist workload and burnout.
Solution
Vista AI Scan applies artificial‑intelligence algorithms to automate the acquisition of cardiac MRI studies, guiding technologists through each step of the protocol. The software optimizes scan parameters in real time, reduces the need for manual adjustments, and standardizes image acquisition across operators and sites. By shortening scan duration and minimizing repeat exams, the platform increases scanner utilization and opens additional appointment slots without additional hardware. Integrated quality‑control checks ensure reproducible, diagnostic‑grade images, allowing clinicians to rely on consistent data for interpretation. The solution works with existing MRI scanners and fits into current workflow tools, delivering productivity gains while easing technologist burden.
Target Audience
The primary customers are radiology and cardiology imaging departments in hospitals, outpatient imaging centers, and specialty cardiac MRI programs that need to increase scan capacity while maintaining high image quality.
Features
- AI‑driven protocol selection and automatic parameter optimization for cardiac MRI sequences
- Real‑time visual guidance overlay that directs slice positioning, breath‑hold timing, and contrast timing
- Automated planning of cardiac views (e.g., short‑axis, long‑axis) using deep‑learning segmentation of anatomy
- Adaptive breath‑hold management that adjusts acquisition windows based on patient performance
- Built‑in image quality metrics and instant feedback to flag suboptimal scans before patient leaves the table
- Seamless integration with major MRI vendor consoles and PACS/RIS via standard DICOM and HL7 interfaces
- Centralized analytics dashboard showing throughput, scan time reductions, and consistency statistics across sites
- Secure, HIPAA‑compliant data handling with optional cloud‑based storage for remote monitoring and reporting