Segmentation of cam-type femurs from CT scans

Abstract

We introduce a new way to accurately segment cam-type pathological femurs from pelvic CT scans. The femur is a difficult target for segmentation due to its proximity to the acetabulum, irregular shape and the varying thickness of its hardened outer shell. In addition, the pathological femurs with femoral-acetabular impingements have a non-standard shape, which increases segmentation difficulty. We overcome these difficulties by (a) dividing the femur into two rounds of segmentation—one for the femur head and another for the body—(b) pre-processing the CT scan to reduce anatomical sources of error (c) two modes of segmentation—a rough estimation of a contour and another for fine contours. Segmentations of the CT volume are performed iteratively, on a slice-by-slice basis and contours are extracted using the morphological snake algorithm. Our methodology was designed to require little initialization from the user and to deftly handle the large variation in femur shapes, most notably from deformations attributed to cam femoral–acetabular impingements. Our efforts are to provide physicians with a new tool that creates patient-specific and high-quality 3D femur models while requiring much less time and effort. Femur models segmented with our method had an average volume overlap error of 2.71±0.44% and symmetric surface distance of 0.28±0.04 mm compared to ground truth models.