  Alignment of the bones in standing position provides useful information in
surgical planning. In total hip arthroplasty (THA), pelvic sagittal inclination
(PSI) angle in the standing position is an important factor in planning of cup
alignment and has been estimated mainly from radiographs. Previous methods for
PSI estimation used a patient-specific CT to create digitally reconstructed
radiographs (DRRs) and compare them with the radiograph to estimate relative
position between the pelvis and the x-ray detector. In this study, we developed
a method that estimates PSI angle from a single anteroposterior radiograph
using two convolutional neural networks (CNNs) without requiring the
patient-specific CT, which reduces radiation exposure of the patient and opens
up the possibility of application in a larger number of hospitals where CT is
not acquired in a routine protocol.
