University of Oulu and Oulu University Hospital develop new ultrasound applications – including artificial intelligence
The study will develop and implement new ultrasound techniques, such as elastography, microvascular Doppler imaging, contrast-enhanced ultrasound and AI-based analysis methods. The goal is to improve diagnostic accuracy and reduce the need for more expensive imaging examinations.
In Finnish healthcare, the use of ultrasound in muscle and tendon problems has remained limited, even though the technology of the devices has advanced significantly in recent years. At the same time, expensive MRI scans are increasingly performed, placing a burden on healthcare and increasing costs.
“In many cases, modern ultrasound can provide sufficiently accurate information already at the initial stage of examination,” says Professor of Radiology and musculoskeletal radiologist Mika Nevalainen.
The research project is developing ultrasound methods capable of detecting tendon inflammation and structural changes more precisely than traditional imaging techniques. Elastography and microvascular Doppler imaging, for example, can reveal tissue stiffness and inflammatory activity in ways that are not always visible in conventional MRI scans.
The study also aims to improve the diagnosis of soft tissue tumours. Currently, up to one-third of tumours remain indeterminate even in MRI, often leading to biopsy or surgery. Combining modern ultrasound techniques with artificial intelligence could help differentiate tumour types at an earlier stage and reduce the need for invasive procedures.
In addition, the project is developing new AI algorithms capable of identifying and characterising tendon disorders, osteoarthritic changes and soft tissue tumours.
“Artificial intelligence is already used in many other areas of ultrasound, but solutions suitable for musculoskeletal imaging are still lacking,” says Professor of Medical Technology Simo Saarakkala.
The project aims to strengthen the role of ultrasound in Finnish radiology and improve diagnostic accessibility, accuracy and cost-effectiveness.