AI service — AI Medical · Ultrasound
Ultrasound analysis
Classify, segment and enhance ultrasound images with models built for the modality rather than adapted from photography.
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.
Ultrasound is operator-dependent and noisy, which is why general-purpose vision models underperform on it. These models are pretrained on ultrasound specifically, and return disease classification, tissue segmentation or an enhanced image.
Images and clips arrive from your device export or archive and come back as masks, classes or enhanced frames. Prompted segmentation is the usual starting point because it needs no training to produce a usable mask.
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 ultrasound 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
- Structure measurement — Segment tissue and lesions so a diameter or area is measured rather than estimated.
- Archive classification — Score a recorded ultrasound archive for a specific finding.
- Image enhancement — Improve frame quality before a reading or measurement step.
More Ultrasound services
- Retinal image analysisRetinal image analysis service →
- Skin lesion analysisSkin lesion analysis service →