  Image segmentation some of the challenging issues on brain magnetic resonance
image tumor segmentation caused by the weak correlation between magnetic
resonance imaging 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.Brain Magnetic Resonance
Imaging segmentation is a complex problem in the field of medical imaging
despite various presented methods.MR image of human brain can be divided into
several sub-regions especially soft tissues such as gray matter,white matter
and cerebra spinal fluid.Although edge information is the main clue in image
segmentation,it cannot get a better result in analysis the content of images
without combining other information.Our goal is to detect the position and
boundary of tumors automatically.Experiments were conducted on real
pictures,and the results show that the algorithm is flexible and convenient.
