Range data pre-processing for the evaluation of torso shape and symmetry in scoliosis

Pre-processing range scans of the human torso for evaluating shape and symmetry changes in scoliosis are non-trivial. First, stray points from surrounding artefacts are often arbitrarily positioned and not amenable to automatic removal. Second, the asymmetrical alignment of the arms and neck makes cropping them difficult. Third, despite a plethora of methods, removal of holes by surface approximation for this niche application remains a challenge particularly in obscure regions like the sides and armpits. This paper proposes a novel surface approximation method and incorporates it into an integrated procedure for pre-processing range scans of the torso that includes interactive tools for cropping stray points and extremities. The new method, spline-fitted moving least squares (MLS), makes use of the Bezier curve and MLS algorithms. Numeric and clinical tests on scans of 30 volunteers, with and without scoliosis, show that the proposed method outperforms its constituent methods and a commercially available graphics package for this application.