Distortion detection of a support implant for artificial hip joint using multiscale matching algorithm

Support implant has been used to reconstruct an artificial hip joint on the acetabulum in total hip arthroplasty (THA). After THA, we should diagnose periodically state of the support implant because the implants may be distorted or broken. This paper proposes an in vivo evaluation method using multidetector-row computed tomography (MDCT) images. The proposed method estimates the distortion degree of the support implant by comparing the 3D geometric model of the support implant with the support implant region segmented from the MDCT images. The support implant region is segmented from the MDCT images using a fuzzy object model which can express knowledge about the shape of objects. The distortion degree is estimated based on a multiscale matching algorithm. The performance of estimating the distortion degree was validated through computer simulation experiments, phantom experiments in vitro, and subject experiments.