  Advances in computing technology have allowed researchers across many fields
of endeavor to collect and maintain vast amounts of observational statistical
data such as clinical data, biological patient data, data regarding access of
web sites, financial data, and the like. This paper addresses some of the
challenging issues on brain magnetic resonance (MR) image tumor segmentation
caused by the weak correlation between magnetic resonance imaging (MRI)
intensity and anatomical meaning. With the objective of utilizing more
meaningful information to improve brain tumor segmentation, an approach which
employs bilateral symmetry information as an additional feature for
segmentation is proposed. This is motivated by potential performance
improvement in the general automatic brain tumor segmentation systems which are
important for many medical and scientific applications
