Local Processing for Complete Data Security 

When cvi42 processes imaging data, everything takes place within the customer’s secure environment. All image data and derived results are managed locally, whether on a hospital workstation or through a customer-managed server installation. No data is ever transmitted outside the institution. 

This architecture ensures compliance with strict hospital IT policies and data protection frameworks. For clinical users, this means AI-powered results without any compromise to data privacy or network security. 

The Circle AI Engine: Trained, Validated, and Frozen 

 “Each of the AI models powering cvi42 is architected and developed within Circle’s controlled research and development environment. Circle’s data science and clinical AI research teams use diverse and representational datasets to train and validate each algorithm. The process typically involves supervised learning, where the AI learns to recognize patterns and structures such as the left ventricle, myocardium, or aortic root by comparing its results to expert-annotated data. 

Once performance meets clinical and regulatory standards, the AI model is locked, “frozen” and encrypted during its integration within cvi42. This means the model’s behavior is fixed, it does not continue to learn or change once deployed at a customer site. The model you use in cvi42 is the validated version approved for clinical use, ensuring consistent and reproducible results across all installations.

No Learning from Customer Data 

It is important to clarify: the AI in cvi42 does not learn from any data processed at the customer site. The algorithm applies its pre-trained parameters to each image set locally. It does not store patient data, send information externally, or modify its internal model based on what it sees or whether a user edits its outputs. Each analysis is isolated, ensuring the AI’s decisions remain consistent and the patient’s information stays protected within the facility’s network. 

How the AI Analyzes Medical Images 

At a technical level, cvi42’s AI is a deep learning-based image analysis engine trained to recognize and segment cardiac anatomy on MR and CT images. Primarily using convolutional neural networks, it performs pixel- or voxel-level classification to delineate key structures, including the endocardial and epicardial borders. These segmentations enable the measurements of clinically relevant metrics such as chamber volumes, ejection fraction, and myocardial mass. 

This process mimics how expert readers would interpret the same dataset, but it happens in seconds and with objective consistency across cases. 

Designed for Trust, Built for Performance 

AI in cvi42 is designed to automate routine analysis while keeping clinicians fully in control. Users can review, adjust, and approve AI-generated contours as needed, ensuring that results always meet their clinical standards. Combined with local data processing, frozen AI models, and Circle’s rigorous training pipeline, this approach delivers accuracy and reliability without ever compromising patient privacy. 

Artificial intelligence (AI) is transforming cardiovascular imaging, helping clinicians analyze complex data faster and with greater consistency. Circle Cardiovascular Imaging’s cvi42 integrates advanced AI models to automate tasks such as segmentation, measurement, and contouring across cardiac MR and CT scans. But just as important as what the AI does is how it works behind the scenes: where the data is processed, what happens to that data, and how the AI itself behaves in the clinical environment.