Asymmetry quantization and application to human mandibles

All biological objects exhibit some degree of asymmetry, but for some parts of the human body, excessive asymmetry is a sign of pathology. Hence, the problem is to draw the line between categorization of objects being too asymmetric and objects exhibiting normal asymmetry. With a measure of asymmetry, the statistics on asymmetry for normal and pathological anatomical structures can be compared. Symmetry is a well-known mathematical group theoretical concept. In this paper, we will mathematically define the concept of weak symmetry, including topological symmetry, which serves as a basis for quantizing asymmetry. The methodology is based on non-rigid registration in the sense that the "size" of a diffeomorphism describes the amount of asymmetry. We will define this size in terms of the minimum biological work needed. That is, we evaluate how much work the biological system must carry out in order to make the object symmetrical; or identically, how much work has been carried out in order to make the ideal symmetrical object into the current (slightly) asymmetrical object. The quantization of asymmetry is validated on a set of normal (assumed near symmetrical) mandibles, and a set of pathological assumed non-symmetric mandibles exhibiting a statistically significant increase of asymmetry.

[1]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[2]  G. Christensen,et al.  k 3D Deformable Magnetic Resonance Textbook Based on Elasticity , 1994 .

[3]  Ruzena Bajcsy,et al.  Multiresolution elastic matching , 1989, Comput. Vis. Graph. Image Process..

[4]  Isabelle Bloch,et al.  Brain symmetry plane computation in MR images using inertia axes and optimization , 2002, Object recognition supported by user interaction for service robots.

[5]  Yanxi Liu,et al.  Robust midsagittal plane extraction from normal and pathological 3-D neuroradiology images , 2001, IEEE Transactions on Medical Imaging.

[6]  Michael I. Miller,et al.  Landmark matching via large deformation diffeomorphisms , 2000, IEEE Trans. Image Process..

[7]  Tron A. Darvann,et al.  Midsagittal surface measurement of the head: an assessment of craniofacial asymmetry , 1999, Medical Imaging.

[8]  G. Christensen,et al.  Consistent nonlinear elastic image registration , 2001, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2001).

[9]  René Thom,et al.  Structural stability and morphogenesis - an outline of a general theory of models , 1977, Advanced book classics.

[10]  Max A. Viergever,et al.  A survey of medical image registration , 1998, Medical Image Anal..

[11]  T. M. Graber,et al.  Normal and abnormal growth of the mandible: A synthesis of longitudinal cephalometric implant studies over a period of 25 years , 1983 .

[12]  Dinggang Shen,et al.  An energy of asymmetry for accurate detection of global reflection axes , 2001, Image Vis. Comput..

[13]  Sébastien Ourselin,et al.  Computation of the mid-sagittal plane in 3-D brain images , 2002, IEEE Transactions on Medical Imaging.

[14]  D. Kendall MORPHOMETRIC TOOLS FOR LANDMARK DATA: GEOMETRY AND BIOLOGY , 1994 .

[15]  Morten Bro-Nielsen,et al.  Fast Fluid Registration of Medical Images , 1996, VBC.

[16]  S. Kreiborg,et al.  Craniofacial morphology and growth in infants and young children with cleft lip and palate , 2002 .

[17]  Mads Nielsen,et al.  Non-rigid registration by geometry-constrained diffusion , 1999, Medical Image Anal..

[18]  David Rey,et al.  Symmetrization of the Non-rigid Registration Problem Using Inversion-Invariant Energies: Application to Multiple Sclerosis , 2000, MICCAI.