Magnetic Resonance Imaging(MRI) is a distinctly important technology of medical imaging, which is widely used in the diagnosis and treatment of tissues and organs of the human body. In the clinical diagnosis of brain tumor, it is a challenge for how to achieve effective automatic brain image segmentation. Multiple Self-Organizing feature Maps(SOM) are utilized to create a Concurrent Self-Organizing Map(CSOM) for the whole segmentation process to realize the brain tumor image segmentation. The results show that CSOM model used in the brain tumor image segmentation is effective and successful in this design, improving the precision and reducing the segmentation duration triumphantly, makes a progressive step to the automated segmentation.