EchoLearn
EchoLearn connects live ultrasound imaging with AI-derived image-quality and geometric assessments, and turns model outputs into visual feedback while the operator scans. Developed at the THRIVE Centre, University of West London, the platform is now in supervised evaluation in an NHS echocardiography training setting.
| Clinical evaluation | Platform | Focus |
|---|---|---|
| Phase 1 clinical evaluation under way: supervised scanning in an NHS training setting since August 2026 | Existing research prototype: live ultrasound video, AI image assessment and on-screen feedback | Acquisition quality, training and operator feedback |
EchoLearn enters Phase 1 clinical evaluation. Supervised scanning sessions with medical students began in August 2026 at Hammersmith Hospital. Read the announcement.
The Challenge
Operator-dependent acquisition quality
Echocardiographic image acquisition is operator dependent. Choosing an appropriate acoustic window and optimising probe position, orientation and angulation require technical skill and adaptation to each patient's anatomy. Image-quality errors can affect both interpretation and downstream measurements. EchoLearn investigates whether immediate, objective feedback can help operators recognise and correct suboptimal acquisitions while they learn to scan.
From live scan to on-screen feedback
How EchoLearn Works
Acquire
A user acquires live echocardiographic images on a compatible ultrasound system.
Assess
AI modules analyse the video and generate image-quality and geometric indicators.
Guide
The platform presents interpretable visual feedback to support acquisition decisions.
Review
Where enabled, session data support review and research into training workflows.
Platform capabilities
A Working Research Platform
EchoLearn provides a research environment for integrating AI-based image assessment with real-time echocardiography acquisition and operator feedback. The platform is being extended to support additional research applications.
Where each capability currently stands:
Currently available
- Live echocardiographic video input
- AI-based image assessment
- On-screen graphical feedback
- Session capture and analysis
Being explored
- Use by medical students in supervised scanning
- Usability and fit with training
- How operators respond to feedback
- Whether real-time guidance helps a novice acquire better images
Future directions
- Longitudinal trainee progress tracking
- Deployment across ultrasound systems
Clinical evaluation
Clinical Evaluation Underway
Supervised evaluation began in August 2026 in an echocardiography training setting at Hammersmith Hospital. Medical students use EchoLearn during supervised scanning sessions. The Phase 1 clinical evaluation asks whether real-time guidance helps a novice operator acquire better images, alongside usability and how operators respond to feedback.
A later controlled evaluation is intended to test whether AI feedback improves acquisition quality, acquisition time, reproducibility and downstream measurements. Results will be published after analysis and review. Improved clinical performance has not yet been shown.
Research-ready infrastructure
Research-Ready Infrastructure
EchoLearn sits within the THRIVE and UNITY echocardiography research ecosystem. THRIVE provides GPU computing, technical expertise and clinical research links. EchoLearn extends the resources below into a live acquisition and feedback environment.
| EchoForge | UNITY | EchoLearn |
|---|---|---|
| Reusable AI model resources for echocardiography. EchoForge |
Expert annotation and dataset infrastructure. UNITY Biobank |
A live acquisition and feedback environment for prospective evaluation, built on these resources. |
People and organisations
Partnerships
- Lead Institution: THRIVE Centre (UWL)
- Clinical partner: National Heart and Lung Institute
- Clinical evaluation setting: Hammersmith Hospital
Work with us
Collaboration & Contact
We welcome conversations with echocardiography educators, NHS training programmes, and researchers interested in image quality, operator guidance and independent evaluation.
For enquiries contact: Massoud Zolgharni or [email protected]
Related: EchoForge | UNITY Biobank