Femur Bone Segmentation Using a Pressure Analogy

It has been recently shown that preclinical analysis of computed tomography 3D image volumes can provide essential information to find the optimal position of an implant in hip replacement procedures. In order to extract such data, proper segmentation is crucial. Many of the currently-available methods depend on manually segmented data as the first step. Inherent difficulties concern the similar density of adjacent structures, and that physically-separated structures appear to touch in scanned imagery. In this study, we describe a new technique based on pressure analogy that depends on the local features of the image to accurately and automatically segment and visualize the femur bone and separate it from the acetabulum. The Dice coefficient was employed to study the similarity between the surface area of the segmentations compared with the manually segmented data, and a high value has been achieved. The same method also showed promising results in segmenting other limbs such as the pelvis, tibia and fibula bones.