Background
Medical imaging is central to modern healthcare; supporting prevention, diagnosis, treatment, and follow-up of countless diseases. Yet access remains limited. Barriers include the high cost of imaging devices, the need for trained specialists to operate them, and the expertise required to interpret results.
As a consequence, imaging is often restricted to hospitals, leaving many patients without timely access. The growing shortage of healthcare workers adds to the challenge: rising demand for imaging services is placing heavy strain on radiologists and specialists, contributing to burnout and threatening the sustainability of care.
Aim
The AI4AI project is harnessing artificial intelligence to make medical imaging more accessible, efficient, and sustainable. Our goals are to:
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Empower non-specialists to safely operate advanced imaging equipment.
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Enhance the quality of images captured with affordable, portable devices.
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Automate the analysis and interpretation of medical images to support decision-making.
By enabling general practitioners, sonographers, and specialist nurses to use imaging tools effectively, we aim to reduce reliance on highly specialized experts. This shift brings diagnostics closer to patients, shortens waiting times, reduces unnecessary hospital visits, and ensures more targeted referrals.
At DIAG, we work on use case G: Urgent Care Referral, specifically focusing on developing robust AI solutions for ultrasound in pulmonary examinations. Beyond technology development, we are also studying the global state of AI integration in healthcare systems, with a particular focus on low- and middle-income countries. Our aim is to identify challenges, highlight opportunities, and present actionable recommendations for stakeholders at all levels; helping to maximize patient outcomes and ensure equitable access to the benefits of AI-driven healthcare.
This project is being undertaken in collaboration with Delft Imaging
Funding
AI4AI receives funding from the Dutch Research Council (NWO).
