Fig. 3

Machine learning model to detect osteolysis in a plain knee radiograph. Labelled input radiographs of healthy and pathological knees are given to the system. The training model then decomposes these images into grey value pixels. The model defines edges at areas of transition from higher to lower grey values. These edges are then aligned with the already-learned anatomy of a healthy knee radiograph. This feature extraction process involves identifying and capturing essential healthy and pathological knee characteristics. Aberrant lines are finally marked and labelled as pathologic. For the model creation, this process is repeatedly iterated to improve the diagnostic value of the model further