Accurate robust symmetry estimation

Abstract

There are various applications, both in medical and nonmedical image analysis, which require the automatic detection of the line (2D images) or plane (3D) of reflective symmetry of objects. There exist relatively simple methods of finding reflective symmetry when object images are complete (i.e., completely symmetric and perfectly segmented from image “background”). A much harder problem is finding the line or plane of symmetry when the object of interest contains asymmetries, and may not have well defined edges. A major area of interest is brain image analysis; there are various reasons why one would want to be able to automatically, robustly and accurately find the (sagittal) mid-plane from a 3D brain image. Example applications include pre-alignment (or sanity checking) for standard registration methods, mid-plane finding as part of symmetric probabilistic anatomical map generation, and, in particular, symmetry-based analyses (e.g., for schizophrenia research). This paper describes EROS - Extraction of Robust Orientation using Symmetry, which has been developed to solve this problem. It has been shown to work with MRI (T1, T2, EPI), PET, SPECT and CT, using robust measures to give accurate results even with images containing large asymmetries.