Knee osteoarthritis (KOA) is a painful and disabling joint disease, involving many structures of the knee. It is often difficult to diagnose, especially in early and mild stages because diagnostic criteria exclude these conditions. X-ray is currently used for doubtful cases, but this imaging tool is unable to reveal most of the early-stage KOA characteristics.
Ultrasound (US) provides a reliable solution to this imaging challenge. US also has the benefit that it is accessible and can even be used at the general practitioner for immediate diagnosis and start of treatment. However, this requires extensive training to acquire and interpret the ultrasound images which complicates broad adaption by General practitioners.
In this project, we will try to overcome this problem by developing an AI-based point-of-care ultrasound device. This device will enable detection of knee osteoarthritis at the general practicioner and will minimize the required training.