Application of statistical shape models in orthopedics: a narrative review

Abstract

Statistical shape models (SSMs) are effective for image processing and analysis and have been used in various medical fields, including face recognition and cranial bone recognition. In orthopedics, SSMs are being used in numerous applications, such as automated segmentation of medical images, preoperative planning, intraoperative navigation combined with robotics, simulation reconstruction of defects, human biomechanics research, description of anatomical shape changes, and prosthesis design. This review highlighted the wide range of applications while acknowledging the diversity of methodologies and techniques encompassed by SSMs, including Gaussian process models and nonlinear solutions. In addition, the available software packages for constructing shape models, such as Scalismo, ShapeWorks, and Deformetrica, were discussed.