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Modeling for Rehabilitation of Collapsing Femoral Head Based on 3D Statistical Shape Knowledge

This paper presents a novel approach for rehabilitation of the collapsing femoral head caused by ANFH from computer tomography (CT) images based on 3D statistical shape model. The shape knowledge about the biological variability of anatomical objects is fundamental for statistical shape analysis and discrimination between healthy and pathological structures. So we integrate the variability of an object population into generation of a characteristic 3D shape model by statistical shape analysis from a training set firstly. Then, after initialization, a suited model is selected automatically to fit the volume data of patient. In the end, the reconstruction is accomplished by an iterative processing of searching and registration between prior models and original data set, in which the surface of femoral head is resurfaced and rehabilitates its original shape. Several experimental results demonstrate the proposed method's performance and efficacy.