We propose to use statistical shape and appearance modelling to classify the proximal femur in hip radiographs of children into Legg-Calvé-Perthes disease and healthy. Legg-Calvé-Perthes disease affects the femoral head with avascular necrosis, which causes large shape deformities during the growth-stage of the child. Further, the dead or dying bone of the femoral head is prominent visually in radiographic images, leading to a distinction between healthy bone and bone where necrosis is present. Currently, there is little to no research into analysing
the shape and appearance of hips affected by Perthes disease from radiographic images. Our research demonstrates how the radiographic shape, texture and overall appearance of a proximal femur affected by Perthes disease differs and how this can be used for identifying cases with the disease. Moreover, we present a radiograph-based fully automatic Perthes classification system that achieves state-of-the-art results with an area under the receiver operator characteristic (ROC) curve of 98%.