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Automated measurement of anterior and posterior acetabular sector angles

In this paper, we propose a segmentation algorithm by which anatomical landmarks on the pelvis are extracted from computed tomography (CT) images. The landmarks are used to automatically define the anterior (AASA) and posterior acetabular sector angles (PASA) describing the degree of hip misalignment. The center of each femoral head is obtained by searching for the point at which most intensity gradient vectors defined at edge points intersect. The radius of each femoral head is computed by finding the sphere, positioned at the center of the femoral head, for which the normalized sum of gradient vector magnitudes on the sphere surface is maximal. The anterior and posterior corners of each acetabulum are searched for on a curve representing the acetabulum and defined by dynamic programming. The femoral head centers and anterior and posterior corners are used to calculate the AASA and PASA. The algorithm was applied to CT images of 120 normal subjects and the results were compared to ground truth values obtained by manual segmentation. The mean absolute difference (± standard deviation) between the obtained and ground truth values was 1.3 ± 0.3 mm for the femoral head centers and 2.1 ± 1.3 degrees for the acetabular angles.