Bone Age Assessment Based on Salient Object Segmentation

Predicting bone age has become pivotal to measure developmental disorder and endocrinology in children. Traditional procedures such as Greulich–Pyle and Tanner-Whitehouse have been used intensively to measure bone age. Recently, several proposed deep learning algorithms show high statistical predictions compared to the traditional assessment practice. However, the commonly used hand x-ray data in ...