Abstract
The precise segmentation of Magnetic Resonance Images (MRI) is an important subject in both medical and computer science communities. With MRI?s property of multi-spectrum, we use the information from its PD-,T1-,and T2-weighted images, mapping them into a multi-dimensional intensity space and getting its vector gradient. Through the improvement of the step function, an unsupervised Self-Organizing Map (SOM) neural network is trained dynamically. To improve the effectiveness of segmentation, we develop a semi-supervised training scheme at the edge of image in multi-dimensional intensity space.