AI service — AI Medical · Cardiology
Cardiac MRI analysis
Segment the ventricles and myocardium on cine cardiac MRI and derive volumes, ejection fraction and condition predictions.
Send us your data volume, throughput and latency targets and any constraint we should design around. You get a proposed configuration, a benchmark on your own data, and a known cost per unit of work before you commit.
Cardiac MRI is the reference standard for chamber volumes, and contouring it by hand is the reason those volumes are not measured more often. Segmentation models return LV, RV and myocardial masks with the derived volumes and ejection fraction attached, at a cost per study low enough to apply to every scan.
Studies arrive as DICOM or NIfTI from your PACS and come back as masks plus a measurement record. Where you hold your own annotated cases, the segmentation model is fitted to them, which is usually what moves accuracy on a local protocol.
Every output is clinical decision support, not a diagnosis: a qualified professional reviews and signs it. Where clinical use requires regulatory approval in your jurisdiction, that approval remains yours to hold — we provide the infrastructure, the model operations and the audit trail behind it.
What we size for
We build the cardiac mri analysis pipeline around the workload you actually have: data format, accuracy target, latency, throughput, concurrency, retention and scheduling. Start with a pilot, then scale production capacity without changing a line of your integration.
Common use cases
- Volumetric reporting — Produce chamber volumes and ejection fraction on every cine study.
- Research cohorts — Contour an entire cohort consistently so measurements compare across cases.
- Condition prediction — Score studies for a list of cardiovascular conditions alongside the measurements.
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