Application of Superpixel Clustering Algorithm to Hip Joint Image Segmentation Registration

Hip fracture is the most common and serious type of fracture in the elderly. The traditional orthopedic disease diagnosis method lacks sufficient information to assist doctors in making a diagnosis, which may easily lead to missed diagnosis and misdiagnosis, delay patient treatment, and may even cause medical accidents. By introducing computer-aided diagnosis technology, this research is mainly divided into the medical image preprocessing process of hip joint diseases, the image segmentation method of superpixel clustering algorithm, the image registration method based on volume feature point selection in the diagnosis of auxiliary ribs of hip joint diseases, and the visualization technology-based method. There are four parts in the evaluation method of auxiliary diagnosis and evaluation of hip joint diseases based on the calculation of quantitative indicators. Segment abdominal CT images through superpixel clustering image processing algorithm to provide auxiliary diagnosis and evaluation of hip joint diseases.