Developmental dysplasia of the hip (DDH) is a developmental deformity occurring in 0.1-3.4% of infants. Timely surgical intervention can ameliorate the condition in stable hips and reduce future cases of osteoarthritis and total hip replacement. However, current definitions of DDH are subjective, and thus would benefit from a more objective and reliable assessment metric. Since the shape of the femoral head and its congruence with the acetabulum are disrupted by DDH, analysis of the femoral head could potentially play a role in the development of novel objective morphological metric for stable DDH. Therefore, this paper aimed to segment the paediatric femoral head in stable hips from radiographs, which has not been attempted before in the chosen focus age group (1-16 years) where the pelvis and hip joint undergo significant development. Two techniques were compared against a baseline U-Net: data augmentation and region-of-interest (ROI) networks. Four models were developed either without, with just one, or with both techniques. Evaluated using tenfold cross-validation, the U-Net trained with both techniques achieved the best results, with a Dice Similarity Coefficient (DSC) of 0.951±0.037 (mean ± standard deviation, calculated with 720 images). Future work will use this segmentation algorithm to accurately characterise hip joint morphology and estimate the benefit of early surgical intervention in DDH.